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市场调查报告书
商品编码
1714728

医疗保健市场中的人工智慧按组件、技术类型、部署模式、应用领域、最终用户和疾病类型划分——2025 年至 2030 年全球预测

Artificial Intelligence in Medicine Market by Component, Technology Type, Deployment Mode, Application Areas, End-User, Disease Type - Global Forecast 2025-2030
出版日期: | 出版商: 360iResearch | 英文 184 Pages | 商品交期: 最快1-2个工作天内

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预计到 2024 年医疗保健人工智慧市场规模将达到 126.4 亿美元，到 2025 年将达到 156.2 亿美元，到 2030 年将达到 468.1 亿美元，复合年增长率为 24.37%。

主要市场统计数据
基准年2024年 126.4亿美元
预计2025年 156.2亿美元
预测年份 2030 468.1亿美元
复合年增长率（%） 24.37%

人工智慧正在透过引入革命性的方法以无与伦比的准确性和速度诊断、治疗和管理疾病，从而迅速改变现代医学的格局。医疗保健专业人员和决策者现在依靠强大的演算法和先进的计算系统不仅可以分析复杂的医疗资料，还可以提供有助于改善患者预后的可行见解。本报告深入研究了医疗保健领域人工智慧的多方面发展，强调了其采用背后的关键驱动因素以及推动产业向前发展的变革性变化。

医疗保健需求与突破性技术应用的整合正在创造一个可以大幅提高临床和营运效率的环境。随着相关人员逐渐接受数位转型，人们越来越重视弥合传统实践与面向未来的技术创新之间的差距。在这个充满活力的生态系统中，人工智慧的整合并不是一个孤立的现象，而是一个触及医疗保健价值链各个层面的系统性变化。

透过全面的研究和严格的分析，本报告旨在透过强调关键趋势、细分见解、区域差异以及引领这些变化的主要企业，成为产业相关人员的宝贵资源。随着该领域的不断成熟，相关人员需要对这些复杂的互动有细緻的理解，以保持竞争力并充分利用人工智慧主导的医疗保健创新的潜力。

变革性变化正在塑造医疗保健领域人工智慧的格局

在人工智慧普及的推动下，医疗保健产业正经历重大变革时期。曾经被认为是未来概念的现在已成为日常医疗保健的关键组成部分，重塑了从诊断到治疗的各个方面。研究、投资和政策变化正在改变行业格局，使人工智慧技术处于医疗创新的前沿。

值得注意的是，这种转变既是服务导向的，也是由软体主导的。一方面，从元件角度详细观察市场，可以发现双重焦点：服务和软体。其中，咨询、整合部署服务经过最佳化，能够更好地适应医疗机构的动态需求。同时，软体发挥着至关重要的作用，应用软体和系统软体为复杂的分析和决策流程提供了所需的技术支援。

除了组件碎片化之外，技术进步也是变革的关键驱动因素。电脑视觉、机器学习、自然语言处理和机器人等技术不仅将重新定义医疗资料的解释方式，还将促进即时决策和个人化医疗。这种整体方法进一步得到了包括云端基础和内部解决方案在内的策略部署的补充，确保医疗保健组织能够优化基础设施成本，同时保持强大的资料安全性和高效能。

人工智慧在医学领域的应用正在扩大，包括诊断、药物发现和治疗方法。诊断领域本身也随着医疗图像和病理检测的创新而取得了进步，从而可以更准确、更早地发现疾病。同时，由于人工智慧技术简化了研究和临床试验，药物研发和治疗性介入介入的努力也正在加速。

这种演变也延伸到对医院、诊所、製药公司和研究机构等最终用户部门的深入了解。这些群体中的每一个都受益于量身定制的人工智慧应用程序，确保技术的部署不仅有效，而且还能满足用户的需求。此外，透过循环系统、皮肤病学、胃肠病学、神经科、妇产科、肿瘤学、整形外科、骨科、小儿科和泌尿系统等疾病类型的详细研究，进一步细化市场策略。这些基于类别的洞察使相关人员能够针对特定的成长和营运改进领域。

整体而言，医疗保健领域人工智慧所经历的变革性变化显示传统范式将发生强有力的重构。它让我们看到了未来的景象：科技增强型医疗保健不仅是一种可能性，而且是提供更精确、更有效率、以病人为中心的照护的标准。

对市场区隔的详细见解

全面了解市场细分对于掌握医疗保健领域人工智慧整合的多面性至关重要。细分框架透过区分内在领域和操作领域，构成了市场分析的支柱。第一个细分基于元件，并深入分析服务和软体。在服务方面，它进一步扩展到咨询主导的策略和整合以及部署解决方案，确保无缝采用人工智慧技术。同时，软体部分经过仔细审查，被细分为处理最终用户介面的应用软体和处理关键后端功能的系统软体。

第二层细分着重于技术类型，透过电脑视觉、机器学习、自然语言处理和机器人技术的视角分析市场。每种技术都将接受评估，以确定其改变特定医疗程序领域的潜力，从解释复杂的诊断影像到根据海量资料集制定精确的治疗计划。这种整体方法使市场参与企业能够发现技术能力与医疗保健需求相符的机会。

考虑实施模式可以进行更详细的分析。我们云端基础的解决方案与内部部署解决方案的评估考虑了可扩展性、安全性和成本效益，为您提供最适合您组织营运框架的选项。

細項分析也延伸到应用领域，对诊断、药物发现和治疗等不同类别进行仔细审查。在诊断领域，值得注意的是，人们特别关注医疗图像和病理检测等子区隔，它们已成为临床决策的关键驱动因素。

同样重要的是对最终用户的详细研究，其中包括各种医疗保健提供者、製药公司和研究机构以及学术中心。在医疗保健提供者中，诊所和医院都受到特别关注，这反映了不同临床环境中采用人工智慧的规模和范围的不同。

最终的细分考虑了疾病类型，从循环系统学到皮肤病学、胃肠病学、神经科、妇产科、肿瘤学、眼科、整形外科、小儿科和泌尿系统。这种分类提供了最有可能从技术干预中受益的临床领域的全面视图，使相关人员能够根据实际疾病流行情况和治疗进展调整他们的研究和投资策略。

综合起来，这些细分见解表明，市场并不是一个整体，而是一个复杂的整体，其中每个组件、技术、部署模式、应用领域、最终用户和疾病类型相互作用，以全面了解人工智慧在医疗保健领域的当前和未来潜力。这种细分的深度和广度为有针对性的策略和及时的干预提供了蓝图，使行业领导者能够做出反映医疗保健领域的当前需求和长期趋势的决策。

目录

第一章 引言

第二章调查方法

第三章执行摘要

第四章 市场概述

第五章 市场洞察

  • 市场动态
    • 驱动程式
      • 世界人口老化正在推动对协助老年人照护和管理的人工智慧解决方案的需求。
      • 个人化医疗需求的不断增长将推动医疗保健领域人工智慧技术的发展
    • 限制因素
      • 医疗领域人工智慧技术的初始采用成本高，且对投资报酬率存在担忧
    • 机会
      • 加强科技公司与医疗保健提供者之间的合作，以开发和部署医疗保健领域的人工智慧
      • 将人工智慧融入机器人手术将提高手术精度、缩短恢復时间并最大限度地降低手术风险
    • 任务
      • 医疗保健领域缺乏接受过人工智慧训练的熟练专业人员
  • 市场区隔分析
    • 技术类型：在医疗保健领域引入机器学习技术，透过资料驱动的洞察改善患者照护结果
    • 最终用户：医院使用人工智慧进行诊断成像和预测分析
  • 波特五力分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会
    • 技术的
    • 合法的
    • 环境

第六章医疗保健市场中的人工智慧（按组成部分）

  • 服务
    • 咨询服务
    • 整合和实施服务
  • 软体
    • 应用软体
    • 系统软体

第七章 医疗保健市场中的人工智慧（依科技类型）

  • 电脑视觉
  • 机器学习
  • 自然语言处理
  • 机器人技术

第八章医疗保健市场中的人工智慧（按部署模式）

  • 云端基础
  • 本地

第九章 医疗保健市场中的人工智慧（按应用领域）

  • 诊断
    • 医学影像
    • 病理检测
  • 药物研发
  • 治疗

第十章 医疗保健市场中的人工智慧（按最终用户）

  • 医疗保健提供者
    • 诊所
    • 医院
  • 製药公司
  • 研究机构和学术中心

第 11 章医疗保健市场中的人工智慧（按疾病类型）

  • 心臟病学
  • 皮肤科
  • 胃肠病学
  • 神经病学
  • 妇产科
  • 肿瘤学
  • 眼科
  • 整形外科
  • 小儿科
  • 泌尿系统

12. 美国医疗保健人工智慧市场

  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美国

13. 亚太地区医疗保健市场人工智慧

  • 澳洲
  • 中国
  • 印度
  • 印尼
  • 日本
  • 马来西亚
  • 菲律宾
  • 新加坡
  • 韩国
  • 台湾
  • 泰国
  • 越南

第十四章欧洲、中东和非洲医疗保健市场中的人工智慧

  • 丹麦
  • 埃及
  • 芬兰
  • 法国
  • 德国
  • 以色列
  • 义大利
  • 荷兰
  • 奈及利亚
  • 挪威
  • 波兰
  • 卡达
  • 俄罗斯
  • 沙乌地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公国
  • 英国

第十五章竞争格局

  • 2024年市场占有率分析
  • 2024年FPNV定位矩阵
  • 竞争情境分析
  • 战略分析与建议

公司名单

  • Aidoc Medical Ltd.
  • Allscripts Healthcare Solutions, Inc.
  • BenevolentAI Limited
  • Butterfly Network, Inc.
  • CloudMedx Inc.
  • Enlitic, Inc.
  • Epic Systems Corporation
  • Exscientia plc
  • Freenome Holdings, Inc.
  • GE Healthcare
  • Google LLC By Alphabet Inc.
  • HeartFlow, Inc.
  • IBM Corporation
  • Insilico Medicine, Inc.
  • Intel Corporation
  • Koninklijke Philips NV
  • Medtronic plc
  • NVIDIA Corporation
  • Owkin, Inc.
  • PathAI, Inc.
  • Qventus, Inc.
  • Recursion Pharmaceuticals, Inc.
  • Siemens Healthineers AG
  • Tempus Labs, Inc.
  • Viz.ai, Inc.
  • Zebra Medical Vision Ltd.
Product Code: MRR-4330CC794AA4

The Artificial Intelligence in Medicine Market was valued at USD 12.64 billion in 2024 and is projected to grow to USD 15.62 billion in 2025, with a CAGR of 24.37%, reaching USD 46.81 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024] USD 12.64 billion
Estimated Year [2025] USD 15.62 billion
Forecast Year [2030] USD 46.81 billion
CAGR (%) 24.37%

Artificial Intelligence is rapidly transforming the landscape of modern medicine by introducing innovative methods to diagnose, treat, and manage diseases with unparalleled precision and speed. Medical professionals and decision-makers are now leveraging powerful algorithms and advanced computing systems that not only analyze complex medical data but also provide actionable insights which help in enhancing patient outcomes. This report provides an in-depth look into the multi-faceted evolution of AI in healthcare, underscoring the major drivers behind its adoption and the transformative shifts propelling the industry forward.

The convergence of healthcare needs with breakthrough technological applications is creating an environment where both clinical and operational efficiencies can be significantly improved. As each stakeholder moves towards embracing digital transformation, there is a growing emphasis on bridging gaps between traditional practices and future-forward technological innovations. In this dynamic ecosystem, the integration of AI is not an isolated phenomenon but a systemic change that touches on all levels of the healthcare value chain.

Through comprehensive research and rigorous analysis, this report aims to serve as a valuable resource for industry professionals by highlighting key trends, segmentation insights, regional variations, and the leading companies spearheading these changes. As the field continues to mature, stakeholders must develop a nuanced understanding of these complex interactions to stay competitive and harness the full potential of AI-driven healthcare innovations.

Transformative Shifts Reshaping the AI in Medicine Landscape

The healthcare industry is undergoing a seismic transformation driven by the pervasive adoption of Artificial Intelligence. What was once seen as a futuristic concept is now a crucial component of everyday healthcare, reshaping every facet from diagnostics to treatment. The industry landscape has shifted as research, investment, and policy revisions place AI technologies at the forefront of medical innovation.

Notably, the transformation encompasses both service-oriented and software-driven elements. On one hand, a detailed study of the market with respect to components reveals a dual focus: services and software. Within services, consulting and integration & deployment services are being optimized to better adapt to the dynamic needs of healthcare institutions. On the other hand, software plays a pivotal role, with applications software and system software providing the technical backbone required for complex analyses and decision-making processes.

In addition to component segmentation, technological evolution underlines a critical driver of transformation. Technologies such as computer vision, machine learning, natural language processing, and robotics are not only redefining how medical data is interpreted but are also facilitating real-time decision-making and personalized care. This holistic approach is further complemented by strategic deployment modes that include both cloud-based and on-premise solutions, ensuring that healthcare organizations can optimize infrastructure costs while maintaining robust data security and high performance.

Application areas of AI in medicine have expanded to include diagnostics, drug discovery, and treatment methodologies. The diagnostic domain itself has seen advancements through medical imaging and pathology detection innovations, thereby enabling more accurate and early detection of diseases. In parallel, efforts in drug discovery and therapeutic interventions are being accelerated by AI-powered techniques that streamline research and clinical trials.

This evolution extends to a refined understanding of end-user sectors such as hospitals, clinics, pharmaceutical companies, and research institutes. Each of these groups benefits from tailored AI applications, ensuring that the deployment of technology is not only effective but also specifically aligned with user needs. Moreover, a detailed exploration of disease types including cardiology, dermatology, gastroenterology, neurology, obstetrics & gynecology, oncology, ophthalmology, orthopedics, pediatrics, and urology has further refined market strategies. These category-based insights enable stakeholders to target specific areas for growth and operational enhancement.

Overall, the transformative shifts observed in AI within the medical realm signal a robust reconfiguration of traditional paradigms. They offer a glimpse into a future where technology-enhanced healthcare isn't just a possibility but a standard, offering more precise, efficient, and patient-centric care.

In-Depth Insight into Market Segmentation

A comprehensive understanding of market segmentation is essential to grasp the multifaceted nature of AI's integration into healthcare. The segmentation framework forms the backbone of market analysis by differentiating between the intrinsic and operational domains. The first segmentation, based on component, takes an analytical deep dive into services and software. The services aspect further branches into consultancy-led strategies and integration plus deployment solutions that ensure seamless adoption of AI technology. Whereas the software segment is meticulously examined by categorizing it into applications software that caters to end-user interfaces and system software which handles critical back-end functions.

The second segmentation layer focuses on technology type, dissecting the market through the lenses of computer vision, machine learning, natural language processing, and robotics. Each technology is evaluated on its potential to transform specific segments of medical procedures, from interpreting complex diagnostic images to formulating precise treatment plans based on vast datasets. This holistic approach enables market participants to identify pockets of opportunity that align technological capabilities with healthcare needs.

Further granularity is achieved by examining the deployment mode. In evaluating cloud-based against on-premise solutions, the analysis takes into account scalability, security, and cost-effectiveness, thereby equipping organizations with the choices that best suit their operational framework.

The segmentation analysis extends into application areas where distinct groups such as diagnostics, drug discovery, and treatment are scrutinized. It is interesting to note that within the diagnostic sphere, there is a pronounced focus on sub-segments like medical imaging and pathology detection, which have emerged as key drivers of clinical decision-making.

Equally important is the detailed study of end-users, which includes a diverse set encompassing healthcare providers, pharmaceutical companies, and research institutes alongside academic centers. Among healthcare providers, both clinics and hospitals are given specific attention, reflecting the varied scale and scope of AI implementation across different clinical settings.

The final segmentation dimension considers disease types, offering insights across a spectrum that ranges from cardiology through dermatology, gastroenterology, neurology, obstetrics & gynecology, oncology, ophthalmology, orthopedics, pediatrics, and urology. This categorization provides an exhaustive view of the clinical areas that stand to benefit most from technological interventions, allowing stakeholders to align research and investment strategies with actual disease prevalence and treatment advancements.

In synthesizing these segmentation insights, it becomes evident that the market is not monolithic but rather a complex tapestry where each component, technology, deployment mode, application area, end-user, and disease type interplays to form a comprehensive understanding of AI's current and future potential in medicine. The depth and breadth of this segmentation offer a roadmap for targeted strategies and timely interventions, allowing industry leaders to make decisions that reflect both immediate needs and long-term trends in the healthcare landscape.

Based on Component, market is studied across Services and Software. The Services is further studied across Consulting Services and Integration & Deployment Services. The Software is further studied across Applications Software and System Software.

Based on Technology Type, market is studied across Computer Vision, Machine Learning, Natural Language Processing, and Robotics.

Based on Deployment Mode, market is studied across Cloud-Based and On-Premise.

Based on Application Areas, market is studied across Diagnostics, Drug Discovery, and Treatment. The Diagnostics is further studied across Medical Imaging and Pathology Detection.

Based on End-User, market is studied across Healthcare Providers, Pharmaceutical Companies, and Research Institutes & Academic Centers. The Healthcare Providers is further studied across Clinics and Hospitals.

Based on Disease Type, market is studied across Cardiology, Dermatology, Gastroenterology, Neurology, Obstetrics & Gynecology, Oncology, Ophthalmology, Orthopedics, Pediatrics, and Urology.

Key Regional Insights Driving Global Trends

Regional trends play a critical role in shaping the overall market dynamics for AI in medicine. Different regions display varied levels of adoption, technological infrastructure, and regulatory environments, each contributing uniquely to the market's evolution. In the Americas, there is a high concentration of healthcare innovation driven by robust funding ecosystems, advanced research facilities, and early technology adoption. This region's ecosystem supports rapid integration of AI-driven solutions into clinical workflows and operational strategies, leading to improvements in patient outcomes and cost efficiencies.

Across Europe, the Middle East, and Africa, regulatory frameworks and public-private partnerships serve as catalysts for technological growth. Investments in technology, bolstered by localized research initiatives, have fostered an environment conducive to both incremental improvements in existing systems and breakthrough innovations. This area emphasizes balanced growth where stringent regulatory measures ensure patient safety while promoting industry-wide advancements in AI applications.

In the Asia-Pacific region, rapid digital transformation is fueled by increasing healthcare demands and a growing population whose needs drive innovative solutions. The region benefits from supportive government policies that encourage technology transfer and collaborative research. These strategies have led to significant advancements in personalized medicine, efficient healthcare delivery, and the overall expansion of AI's footprint in various segments of the healthcare market.

The diverse regional nuances reflect how different factors such as policy frameworks, economic dynamics, and cultural considerations shape market strategies. Stakeholders who understand these regional insights can better navigate the complexities of international markets while tailoring their approaches to maximize local advantages. By leveraging regional strengths and addressing unique challenges, industry leaders are positioned to capitalize on growth opportunities and steer the evolution of AI in medicine on a global scale.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

Comprehensive Analysis of Leading Industry Players

The competitive landscape of AI in medicine is marked by a broad spectrum of companies that are spearheading innovation and market transformation. Various renowned organizations are actively shaping the future of healthcare through breakthrough research, strategic partnerships, and a relentless focus on delivering value. Notable players include Aidoc Medical Ltd., Allscripts Healthcare Solutions, Inc., and BenevolentAI Limited, each contributing robust expertise in technology integration and clinical application. Additional influential companies such as Butterfly Network, Inc. and CloudMedx Inc. are driving advancements in diagnostics and real-time analytics while Enlitic, Inc. and Epic Systems Corporation continue to refine their offerings, ensuring that complex medical data translates into actionable insights.

Further stirring the industry are companies like Exscientia plc and Freenome Holdings, Inc., which have made significant inroads in drug discovery and cancer diagnostics respectively. Solid examples of this trend include GE Healthcare and Google LLC by Alphabet Inc., both harnessing vast swathes of data to optimize medical imaging and operational efficiency. HeartFlow, Inc. and IBM Corporation have also been pivotal in integrating AI technologies into routine clinical analyses, ensuring that the healthcare ecosystem becomes more predictive and responsive.

Other key contributors include Insilico Medicine, Inc., Intel Corporation, and Koninklijke Philips N.V., which are recognized for their innovative approaches to healthcare challenges. Medtronic plc and NVIDIA Corporation are advancing the frontier of medical device innovation with AI-powered capabilities, while companies such as Owkin, Inc. and PathAI, Inc. stand out for their cutting-edge research in pathology and diagnostics. Qventus, Inc. alongside Recursion Pharmaceuticals, Inc. are redefining operational efficiencies and drug formulation techniques, further complemented by the advancements of Siemens Healthineers AG and Tempus Labs, Inc.

Prominent players such as Viz.ai, Inc. and Zebra Medical Vision Ltd. illustrate a continued drive toward making AI accessible in everyday clinical practice. The diverse portfolios and proven track records of these companies underscore not only the technological advances within the medical field but also the importance of strategic positioning and continuous innovation. Their collective efforts are instrumental in bridging the gap between emerging research trends and real-world application, ensuring that AI continues to elevate standards of care across the globe.

The report delves into recent significant developments in the Artificial Intelligence in Medicine Market, highlighting leading vendors and their innovative profiles. These include Aidoc Medical Ltd., Allscripts Healthcare Solutions, Inc., BenevolentAI Limited, Butterfly Network, Inc., CloudMedx Inc., Enlitic, Inc., Epic Systems Corporation, Exscientia plc, Freenome Holdings, Inc., GE Healthcare, Google LLC By Alphabet Inc., HeartFlow, Inc., IBM Corporation, Insilico Medicine, Inc., Intel Corporation, Koninklijke Philips N.V., Medtronic plc, NVIDIA Corporation, Owkin, Inc., PathAI, Inc., Qventus, Inc., Recursion Pharmaceuticals, Inc., Siemens Healthineers AG, Tempus Labs, Inc., Viz.ai, Inc., and Zebra Medical Vision Ltd.. Actionable Recommendations for Industry Leaders

In light of the evolving landscape and multifaceted segmentation detailed above, industry leaders are advised to take several specific steps to secure a competitive advantage and drive sustainable growth. An immediate priority should be the strategic adoption of flexible technology solutions that seamlessly bridge cloud-based and on-premise infrastructures, ensuring both scalability and security. Leaders must explore integrating advanced analytical tools that harness the power of machine learning, computer vision, natural language processing, and robotics. This integrative approach can streamline complex operations and improve clinical outcomes without a steep learning curve or disruptive process changes.

Moreover, it is crucial to align market entry strategies with a strong understanding of regional differences. Companies operating across the Americas, Europe, the Middle East, Africa, and Asia-Pacific should tailor their tactics to address specific regulatory frameworks, healthcare funding models, and patient demographics unique to each region. Establishing localized research initiatives and forging robust collaborations with local healthcare providers and academic institutions can also catalyze innovation and facilitate the easier adoption of AI-driven processes.

Investment in specialized segmentation such as consulting, integration, and advanced system software should be prioritized to maximize operational efficiencies. Industry players would benefit from developing dedicated teams focused on monitoring emerging trends in diagnostics, drug discovery, and treatment, ensuring that strategies remain aligned with the latest scientific and technological breakthroughs.

Concurrently, fostering partnerships with leading technology vendors and research institutions will enable an agile response to rapidly evolving market dynamics. It is advisable to allocate resources toward continuous training programs and workshops to ensure that teams are well-versed in leveraging state-of-the-art AI applications effectively.

Adopting these recommendations, while maintaining a keen focus on both immediate and long-term objectives, will empower industry leaders to not only anticipate future market shifts but also act decisively in harnessing the unprecedented potential of AI to transform healthcare delivery.

Conclusion: Embracing a Future Driven by AI Innovation

In summary, the penetration of Artificial Intelligence into the realm of medicine signifies a paradigm shift that transcends traditional clinical methodologies. Every segment of the market-from service and software components to advanced technology types and nuanced deployment models-demonstrates that AI is not simply an add-on but a crucial catalyst for a complete reengineering of healthcare delivery. Detailed segmentation insights reveal a multi-dimensional space, where innovations in diagnostics, drug discovery, and therapeutic solutions are tailored to meet diverse needs. Furthermore, regional variations and the strategic positioning of leading companies collectively offer a roadmap for sustainable market growth.

Ultimately, the confluence of these trends, dynamics, and actionable recommendations paints a clear picture of a future where technology and medicine converge to offer transformative results. As stakeholders continue to invest in and integrate AI, the trajectory of medical innovation will be characterized by improved patient care, reduced operational friction, and a new era of data-driven clinical excellence. By embracing these shifts, the medical community is poised to lead the charge towards an ecosystem that is both efficient and adaptive to the ever-changing landscape of healthcare.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Global aging demographics are creating a demand for AI solutions to support elderly care and management
      • 5.1.1.2. Increased demand for personalized medicine fuels the growth of AI technologies in healthcare
    • 5.1.2. Restraints
      • 5.1.2.1. High initial implementation costs and ROI concerns for AI technologies in medicine
    • 5.1.3. Opportunities
      • 5.1.3.1. Rising partnerships between technology companies and healthcare providers for developent and adoption of AI in medicine
      • 5.1.3.2. Integration of AI in robotic surgery to enhance precision, reduce recovery times, and minimize surgical risks
    • 5.1.4. Challenges
      • 5.1.4.1. Shortage of skilled professionals trained in artificial intelligence for healthcare
  • 5.2. Market Segmentation Analysis
    • 5.2.1. Technology Type: Adoption of machine leaning technology in medicine for improving patient care outcomes through data-driven insights
    • 5.2.2. End-User: Usage of artificial inteligence in hospitals for diagnostic imaging, and predictive analytics
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. Artificial Intelligence in Medicine Market, by Component

  • 6.1. Introduction
  • 6.2. Services
    • 6.2.1. Consulting Services
    • 6.2.2. Integration & Deployment Services
  • 6.3. Software
    • 6.3.1. Applications Software
    • 6.3.2. System Software

7. Artificial Intelligence in Medicine Market, by Technology Type

  • 7.1. Introduction
  • 7.2. Computer Vision
  • 7.3. Machine Learning
  • 7.4. Natural Language Processing
  • 7.5. Robotics

8. Artificial Intelligence in Medicine Market, by Deployment Mode

  • 8.1. Introduction
  • 8.2. Cloud-Based
  • 8.3. On-Premise

9. Artificial Intelligence in Medicine Market, by Application Areas

  • 9.1. Introduction
  • 9.2. Diagnostics
    • 9.2.1. Medical Imaging
    • 9.2.2. Pathology Detection
  • 9.3. Drug Discovery
  • 9.4. Treatment

10. Artificial Intelligence in Medicine Market, by End-User

  • 10.1. Introduction
  • 10.2. Healthcare Providers
    • 10.2.1. Clinics
    • 10.2.2. Hospitals
  • 10.3. Pharmaceutical Companies
  • 10.4. Research Institutes & Academic Centers

11. Artificial Intelligence in Medicine Market, by Disease Type

  • 11.1. Introduction
  • 11.2. Cardiology
  • 11.3. Dermatology
  • 11.4. Gastroenterology
  • 11.5. Neurology
  • 11.6. Obstetrics & Gynecology
  • 11.7. Oncology
  • 11.8. Ophthalmology
  • 11.9. Orthopedics
  • 11.10. Pediatrics
  • 11.11. Urology

12. Americas Artificial Intelligence in Medicine Market

  • 12.1. Introduction
  • 12.2. Argentina
  • 12.3. Brazil
  • 12.4. Canada
  • 12.5. Mexico
  • 12.6. United States

13. Asia-Pacific Artificial Intelligence in Medicine Market

  • 13.1. Introduction
  • 13.2. Australia
  • 13.3. China
  • 13.4. India
  • 13.5. Indonesia
  • 13.6. Japan
  • 13.7. Malaysia
  • 13.8. Philippines
  • 13.9. Singapore
  • 13.10. South Korea
  • 13.11. Taiwan
  • 13.12. Thailand
  • 13.13. Vietnam

14. Europe, Middle East & Africa Artificial Intelligence in Medicine Market

  • 14.1. Introduction
  • 14.2. Denmark
  • 14.3. Egypt
  • 14.4. Finland
  • 14.5. France
  • 14.6. Germany
  • 14.7. Israel
  • 14.8. Italy
  • 14.9. Netherlands
  • 14.10. Nigeria
  • 14.11. Norway
  • 14.12. Poland
  • 14.13. Qatar
  • 14.14. Russia
  • 14.15. Saudi Arabia
  • 14.16. South Africa
  • 14.17. Spain
  • 14.18. Sweden
  • 14.19. Switzerland
  • 14.20. Turkey
  • 14.21. United Arab Emirates
  • 14.22. United Kingdom

15. Competitive Landscape

  • 15.1. Market Share Analysis, 2024
  • 15.2. FPNV Positioning Matrix, 2024
  • 15.3. Competitive Scenario Analysis
    • 15.3.1. GE HealthCare unveils AI innovation lab to revolutionize medical technology
    • 15.3.2. Stryker's strategic acquisition of care.ai to enhance AI-driven healthcare solutions
    • 15.3.3. GE HealthCare strengthens ultrasound capabilities with AI acquisition
  • 15.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. Aidoc Medical Ltd.
  • 2. Allscripts Healthcare Solutions, Inc.
  • 3. BenevolentAI Limited
  • 4. Butterfly Network, Inc.
  • 5. CloudMedx Inc.
  • 6. Enlitic, Inc.
  • 7. Epic Systems Corporation
  • 8. Exscientia plc
  • 9. Freenome Holdings, Inc.
  • 10. GE Healthcare
  • 11. Google LLC By Alphabet Inc.
  • 12. HeartFlow, Inc.
  • 13. IBM Corporation
  • 14. Insilico Medicine, Inc.
  • 15. Intel Corporation
  • 16. Koninklijke Philips N.V.
  • 17. Medtronic plc
  • 18. NVIDIA Corporation
  • 19. Owkin, Inc.
  • 20. PathAI, Inc.
  • 21. Qventus, Inc.
  • 22. Recursion Pharmaceuticals, Inc.
  • 23. Siemens Healthineers AG
  • 24. Tempus Labs, Inc.
  • 25. Viz.ai, Inc.
  • 26. Zebra Medical Vision Ltd.

LIST OF FIGURES

  • FIGURE 1. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET MULTI-CURRENCY
  • FIGURE 2. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET MULTI-LANGUAGE
  • FIGURE 3. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET RESEARCH PROCESS
  • FIGURE 4. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, 2024 VS 2030
  • FIGURE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, 2018-2030 (USD MILLION)
  • FIGURE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY REGION, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2024 VS 2030 (%)
  • FIGURE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2024 VS 2030 (%)
  • FIGURE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2030 (%)
  • FIGURE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2024 VS 2030 (%)
  • FIGURE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2024 VS 2030 (%)
  • FIGURE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2024 VS 2030 (%)
  • FIGURE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 20. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 21. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 22. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY STATE, 2024 VS 2030 (%)
  • FIGURE 23. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY STATE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 24. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 25. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 26. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 27. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 28. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SHARE, BY KEY PLAYER, 2024
  • FIGURE 29. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

  • TABLE 1. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
  • TABLE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, 2018-2030 (USD MILLION)
  • TABLE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 6. ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET DYNAMICS
  • TABLE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CONSULTING SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY INTEGRATION & DEPLOYMENT SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATIONS SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SYSTEM SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPUTER VISION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 20. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ROBOTICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 21. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 22. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CLOUD-BASED, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ON-PREMISE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 24. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 25. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 26. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY MEDICAL IMAGING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 27. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY PATHOLOGY DETECTION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 28. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 29. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DRUG DISCOVERY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TREATMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 31. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 32. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 33. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CLINICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 34. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HOSPITALS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 35. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 36. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY PHARMACEUTICAL COMPANIES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 37. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY RESEARCH INSTITUTES & ACADEMIC CENTERS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 38. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 39. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY CARDIOLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 40. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DERMATOLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 41. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY GASTROENTEROLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 42. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY NEUROLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 43. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY OBSTETRICS & GYNECOLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 44. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ONCOLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 45. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY OPHTHALMOLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 46. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY ORTHOPEDICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 47. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY PEDIATRICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 48. GLOBAL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY UROLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 49. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 50. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 51. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 52. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 53. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 54. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 55. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 56. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 57. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 58. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 59. AMERICAS ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 60. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 61. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 62. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 63. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 64. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 65. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 66. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 67. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 68. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 69. ARGENTINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 70. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 71. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 72. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 73. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 74. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 75. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 76. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 77. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 78. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 79. BRAZIL ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 80. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 81. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 82. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 83. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 84. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 85. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 86. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 87. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 88. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 89. CANADA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 90. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 91. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 92. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 93. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 94. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 95. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 96. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 97. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 98. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 99. MEXICO ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 100. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 101. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 102. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 103. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 104. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 105. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 106. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 107. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 108. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 109. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 110. UNITED STATES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
  • TABLE 111. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 112. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 113. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 114. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 115. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 116. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 117. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 118. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 119. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 120. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 121. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 122. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 123. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 124. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 125. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 126. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 127. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 128. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 129. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 130. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 131. AUSTRALIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 132. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 133. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 134. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 135. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 136. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 137. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 138. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 139. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 140. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 141. CHINA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 142. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 143. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 144. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 145. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 146. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 147. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 148. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 149. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 150. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 151. INDIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 152. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 153. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 154. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 155. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 156. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 157. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 158. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 159. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 160. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 161. INDONESIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 162. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 163. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 164. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 165. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 166. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 167. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 168. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 169. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 170. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 171. JAPAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 172. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 173. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 174. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 175. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 176. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 177. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 178. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 179. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 180. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 181. MALAYSIA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 182. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 183. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 184. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 185. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 186. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 187. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 188. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 189. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 190. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 191. PHILIPPINES ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 192. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 193. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 194. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 195. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 196. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 197. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 198. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 199. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 200. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 201. SINGAPORE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 202. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 203. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 204. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 205. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 206. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 207. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 208. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 209. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 210. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 211. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 212. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 213. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 214. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 215. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 216. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 217. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 218. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 219. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 220. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 221. TAIWAN ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 222. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 223. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 224. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 225. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 226. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 227. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 228. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 229. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 230. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 231. THAILAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 232. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 233. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 234. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 235. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 236. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 237. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 238. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 239. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 240. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 241. VIETNAM ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 242. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 243. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 244. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 245. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 246. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 247. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 248. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 249. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 250. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 251. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 252. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 253. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 254. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 255. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 256. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 257. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 258. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 259. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 260. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 261. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 262. DENMARK ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 263. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 264. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 265. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 266. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 267. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 268. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 269. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 270. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 271. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 272. EGYPT ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 273. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 274. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 275. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 276. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 277. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 278. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 279. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 280. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 281. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 282. FINLAND ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 283. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 284. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 285. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 286. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY TECHNOLOGY TYPE, 2018-2030 (USD MILLION)
  • TABLE 287. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 288. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 289. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DIAGNOSTICS, 2018-2030 (USD MILLION)
  • TABLE 290. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 291. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY HEALTHCARE PROVIDERS, 2018-2030 (USD MILLION)
  • TABLE 292. FRANCE ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY DISEASE TYPE, 2018-2030 (USD MILLION)
  • TABLE 293. GERMANY ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 294. GERMANY ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 295. GERMANY ARTIFICIAL INTELLIGENCE IN MEDICINE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 296. GERMANY ART