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市场调查报告书
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1715586

医疗保健市场中人工智慧的类型、应用、最终用户和部署模式—2025-2030 年全球预测

Artificial Intelligence in Healthcare Market by Type, Application, End User, Deployment Mode - 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价值将达到 238.3 亿美元，到 2025 年将达到 287.8 亿美元，复合年增长率为 22.13%，到 2030 年将达到 791.3 亿美元。

主要市场统计数据
基准年2024年 238.3亿美元
预计年份：2025年 287.8亿美元
预测年份 2030 791.3亿美元
复合年增长率（%） 22.13%

人工智慧 (AI) 从根本上重塑医疗保健产业，将尖端技术与临床专业知识相结合，提供创新解决方案。人工智慧与医疗保健的整合不仅仅意味着技术进步；这也意味着我们使用数据、做出决策和改善患者结果的方式的转变。在过去的几年里，人工智慧已经从一个未来概念发展成为支持诊断、治疗计划和业务效率的重要工具。这种演变受到几个关键因素的推动，包括医疗保健数据的日益普及、机器学习演算法的突破以及在改善患者照护的同时降低成本的迫切需求。

在这个动态的环境中，相关人员——从临床医生和 IT 专业人员到政策制定者和研究人员——发现自己正处于一个复杂但充满机会的环境中。努力保持竞争力的医疗保健组织面临着提供高品质、个人化护理和确保营运永续性的双重任务。这是一项策略必要事项，它为慢性病管理开闢了新途径，简化了工作流程，并提高了诊断的准确性。

人工智慧在医疗保健领域的变革力量也正在刺激技术创新者和医疗保健提供者之间的合作。这些伙伴关係正在推动支持临床决策、预测分析和日常业务自动化的先进系统的发展。因此，该领域的持续发展需要即时和长期的策略性投资，为更灵活、高效和以患者为中心的医疗保健系统奠定基础。

人工智慧主导的医疗保健解决方案的变革时期

随着人工智慧主导的解决方案成为临床和业务流程不可或缺的一部分，医疗保健领域正在变革时期。机器学习、自然语言处理和电脑视觉领域的重大进步将提供反应速度更快的系统，从而简化诊断、个人化治疗通讯协定并以前所未有的准确度预测患者结果。此外，人工智慧与医疗保健工作流程的整合正在引发模式转移。传统医疗保健正在迅速转向数位化优先的方法，该方法包括自动化和数据主导的决策。

对患者需求的敏感度现已深深融入技术设计中。该系统旨在提供针对具体情况且高度可操作的即时见解。医疗保健组织正在投资这些下一代工具，以改善病患监测、增强临床决策支援并优化资源分配。这种转变不仅限于临床领域；行政和营运领域也从人工智慧主导的效率中受益匪浅，从而降低了开销并简化了病患管理。

在临床测试中，人工智慧不仅可以提高诊断准确性，而且还有助于提高整体护理效率。将先进的数据分析与个人化医疗保健结合，可以产生协同效应，从而提供更快、更可靠的治疗结果。在患者期望不断提高和医疗保健挑战迅速发展的时代，人工智慧主导的解决方案的这种变革性转变有可能重塑医疗保健的未来。

详细的细分洞察推动市场创新

医疗保健人工智慧市场被严格细分为多个部分，以便对其多面性提供细緻的理解。富有洞察力的细分方法从各个观点考虑市场，确保不会忽略任何重要方面。首先，依技术类型分析时，市场大致分为三大类：硬体、服务和软体。硬体部分深入研究监测设备、机器人和穿戴式装置的创新，它们在患者照护和诊断准确性方面发挥着独特的作用。同时，服务部门评估确保人工智慧解决方案无缝运作所需的咨询服务、部署整合服务和维护支援方面。同时，在软体领域，我们检验临床决策支援系统、资料管理和分析工具、药物发现平台、医疗保健影像处理平台和自然语言处理应用程式的开发和实施，每个应用程式都推动增强决策和资料解释的能力。

为了补充这一点，应用程式细分提供了一个将技术与现实世界的医疗保健流程连接起来的框架。在此背景下，市场从疾病诊断、电子健康记录(EHR) 管理、病患监测和治疗的角度进行审查。人工智慧在疾病诊断中的应用正在进一步完善，重点关注癌症检测和慢性病管理等关键领域，展现出透过早期和有针对性的干预来挽救生命的潜力。同时，EHR 管理将受益于资料加密和安全以及患者资料分类方面的进步，以确保敏感资讯得到最谨慎的处理。此外，病患监测技术将在远端患者监护和生命体征监测方面受到严格审查，这反映了业界向优先考虑患者便利的分散护理模式的转变。最后，治疗部分强调了人工智慧在个人化治疗方法和新疗法开发中的重要性。

医疗保健付款人、医疗保健提供者、患者、製药公司和生物技术公司等最终用户的评估进一步丰富了这种详细的细分。每个团体都对如何采用和利用人工智慧技术来满足他们的特定需求提供了独特的见解，无论是控製成本、增强医疗服务还是加速药物开发。最后，根据云端基础、混合和内部部署的解决方案的部署类型进行市场细分，突显了技术基础架构的选择如何推动灵活性和可扩展性。在云端基础的类别中，私有云端和公共云端解决方案的细微差别得到了仔细考虑，特别是在资料安全性、整合速度和成本效益方面。

这种全面的细分可以对市场趋势和创新驱动因素进行细緻的评估，显示所有组成部分是如何相互关联的。透过检查这些层面，行业领导者可以发现成长机会并根据不断变化的市场需求调整他们的策略。最终，这些细分洞察提供了对人工智慧应用进展和挑战的平衡和多方面的视角，推动医疗保健行业走向智慧、个人化和高效的护理未来。

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
      • 全球慢性病盛行率不断上升
      • 扩大人工智慧在临床决策支援系统中的应用并最大限度地减少诊断错误
      • 政府支持将人工智慧融入医疗保健体系的措施和政策
    • 限制因素
      • 将人工智慧工具整合到医疗保健系统中的技术限制
    • 机会
      • 人工智慧整合治疗和诊断工具的持续进步
      • 人工智慧在个人化医疗和个人化治疗计划中的作用日益扩大
    • 任务
      • 医疗保健领域人工智慧相关的资料隐私问题和严格合规要求
  • 市场区隔分析
    • 类型：临床决策支援软体解决方案越来越受欢迎
    • 用途：扩大人工智慧在医疗保健领域疾病诊断的应用
  • 波特五力分析
  • PESTEL分析
    • 政治
    • 经济
    • 社会
    • 科技
    • 法律
    • 环境

第六章 医疗保健市场中的人工智慧（按类型）

  • 介绍
  • 硬体
    • 监控设备
    • 机器人技术
    • 穿戴式装置
  • 服务
    • 咨询服务
    • 实施和整合服务
    • 维护和支援
  • 软体
    • 临床决策支援系统
    • 数据管理与分析
    • 药物研发平台
    • 医疗影像平台
    • 自然语言处理应用

第七章 医疗保健市场中的人工智慧应用

  • 介绍
  • 疾病诊断
    • 癌症检测
    • 慢性病管理
  • EHR管理
    • 资料加密和安全
    • 患者资料分类
  • 病患监测
    • 远端患者监护
    • 生命征象监测
  • 治疗

第八章 医疗保健市场中的人工智慧（按最终用户）

  • 介绍
  • 医疗保险公司
  • 医疗保健提供者
  • 病人
  • 製药和生物技术公司

第九章医疗保健市场中的人工智慧（按部署模式）

  • 介绍
  • 云端基础
    • 私有云端
    • 公共云端
  • 杂交种
  • 本地

10. 美国医疗保健人工智慧市场

  • 介绍
  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美国

11. 亚太地区医疗保健市场人工智慧

  • 介绍
  • 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

12. 欧洲、中东和非洲医疗保健市场中的人工智慧

  • 介绍
  • 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

第十三章竞争格局

  • 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

  • AiCure, LLC
  • Atomwise Inc.
  • Babylon Healthcare Services Ltd
  • Behold.ai Technologies Limited
  • Berg LLC
  • Butterfly Network, Inc.
  • ClosedLoop.ai Inc.
  • GE Healthcare
  • Google, LLC by Alphabet, Inc.
  • Intel Corporation
  • International Business Machines Corporation
  • Koninklijke Philips NV
  • Medasense Biometrics Ltd.
  • Microsoft Corporation
  • Modernizing Medicine, Inc.
  • Nanox Imaging Ltd.
  • Novo Nordisk A/S
  • NVIDIA Corporation
  • Oncora Medical
  • Oracle Corporation
  • Oxipit.ai
  • Recursion Pharmaceuticals
  • Sanofi SA
  • Sensely, Inc.
  • Siemens Healthineers AG
  • Tempus Labs, Inc.
Product Code: MRR-031BF22F9550

The Artificial Intelligence in Healthcare Market was valued at USD 23.83 billion in 2024 and is projected to grow to USD 28.78 billion in 2025, with a CAGR of 22.13%, reaching USD 79.13 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024] USD 23.83 billion
Estimated Year [2025] USD 28.78 billion
Forecast Year [2030] USD 79.13 billion
CAGR (%) 22.13%

Artificial Intelligence (AI) has fundamentally reshaped the healthcare industry, merging cutting-edge technology with clinical expertise to offer innovative solutions. The integration of AI in healthcare represents not only a technological advancement but also a transformation in how data is harnessed, decisions are made, and patient outcomes are improved. Over the past few years, AI has moved from a futuristic concept to an essential tool that supports diagnostics, treatment planning, and operational efficiency. This evolution has been driven by several key factors including the increased availability of healthcare data, breakthroughs in machine learning algorithms, and the pressing need to reduce costs while improving patient care.

In this dynamic environment, stakeholders from clinicians and IT professionals to policymakers and researchers find themselves navigating a complex but opportunity-rich landscape. As healthcare organizations strive to remain competitive, they are compelled by the dual mandate of delivering high-quality, personalized care and ensuring operational sustainability. In this context, AI is more than a technological novelty-it is a strategic imperative that opens new avenues for managing chronic diseases, streamlining workflows, and enhancing diagnostic accuracy.

The transformative power of AI in healthcare has also fostered collaborations between technology innovators and healthcare providers. These partnerships are fueling the development of advanced systems capable of supporting clinical decision-making, predictive analytics, and the automation of routine tasks. As such, the ongoing evolution in this domain invites both immediate and long-term strategic investments, laying the foundation for a healthcare system that is more responsive, efficient, and patient-centered.

Transformative Shifts in AI-Driven Healthcare Solutions

The landscape of healthcare is undergoing transformative shifts as AI-driven solutions become integral to clinical and operational processes. Significant advancements in machine learning, natural language processing, and computer vision are now poised to deliver highly responsive systems that streamline diagnostics, personalize treatment protocols, and predict patient outcomes with unprecedented accuracy. Furthermore, the integration of AI into healthcare workflows has catalyzed a paradigm shift; traditional practices are rapidly giving way to digital-first approaches that embrace automation and data-driven decision-making.

Sensitivity to patient needs is now deeply embedded in technology design; systems are being engineered to provide real-time insights that are both context-specific and highly actionable. As healthcare institutions invest in these next-generation tools, they are witnessing improvements in patient monitoring, enhanced clinical decision support, and the optimization of resource allocation. This transformation is not limited to the clinical domain; administrative and operational spheres are also benefiting extensively from AI driven efficiencies that reduce overheads and streamline patient management.

Clinical trials have increasingly demonstrated that AI not only augments diagnostic precision but also contributes to the overall efficiency of care delivery. The evidence is clear: when you combine advanced data analytics with personalized medicine, you create a synergy that leads to faster, more reliable outcomes. In an era marked by increasing patient expectations and rapidly evolving medical challenges, these transformative shifts in AI-driven solutions hold the promise of reimagining the future of healthcare.

Detailed Segmentation Insights Driving Market Innovation

The healthcare AI market is rigorously dissected into multiple segments that provide a nuanced understanding of its multifaceted nature. An insightful segmentation approach considers the market from various perspectives, ensuring no critical aspect is overlooked. First, when analyzing technology by type, the market is broadly studied across three primary categories-hardware, services, and software. The hardware segment delves into innovations such as monitoring equipment, robotics, and wearable devices, each playing a distinct role in patient care and diagnostic precision. Meanwhile, the services category evaluates the dimensions of consulting services, deployment and integration services, and maintenance and support, all of which are essential for ensuring the seamless operationalization of AI solutions. The software domain, on the other hand, examines the development and implementation of clinical decision support systems, data management and analysis tools, drug discovery platforms, medical imaging platforms, and natural language processing applications, each driving forward the capabilities for enhanced decision-making and data interpretation.

Complementing this, the segmentation based on application provides a framework that links technology with real-world healthcare processes. In this context, the market is reviewed through the lens of disease diagnosis, electronic health record (EHR) management, patient monitoring, and therapeutics. The application of AI in disease diagnosis is further refined by focusing on critical areas such as cancer detection and chronic disease management, showcasing the life-saving potential of early and precise interventions. Concurrently, EHR management benefits from advancements in data encryption and security as well as patient data classification, ensuring that sensitive information is handled meticulously. Further, patient monitoring technologies are scrutinized through the facets of remote patient monitoring and vital sign monitoring, reflecting the industry's shift towards decentralized care models that prioritize patient convenience. Lastly, the therapeutics area underscores the importance of AI in developing personalized treatment regimens and novel therapeutic agents.

This in-depth segmentation is further enriched by evaluation based on end users, which include healthcare insurers, healthcare providers, patients, and pharmaceutical as well as biotech companies. Each group offers unique insights into how AI technologies are being adopted and leveraged to meet their respective needs, whether that be cost containment, enhanced care delivery, or accelerated drug development. Finally, the market's segmentation according to deployment mode-spanning cloud-based, hybrid, and on-premise solutions-reveals how technology infrastructure choices are driving flexibility and scalability. Within the cloud-based category, the nuances of private and public cloud solutions are carefully considered, particularly in light of data security, integration speed, and cost efficiencies.

This comprehensive segmentation allows for a granular assessment of market trends and innovation drivers, illustrating a landscape where every component is interconnected. By examining these layers, industry leaders can pinpoint growth opportunities and tailor their strategies in alignment with evolving market demands. Ultimately, these segmentation insights provide a balanced and multifaceted view of the advancements and challenges in AI adoption, propelling the healthcare industry toward a future defined by intelligent, personalized, and efficient care.

Based on Type, market is studied across Hardware, Services, and Software. The Hardware is further studied across Monitoring Equipment, Robotics, and Wearable Devices. The Services is further studied across Consulting Services, Deployment & Integration Services, and Maintenance & Support. The Software is further studied across Clinical Decision Support Systems, Data Management & Analysis, Drug Discovery Platforms, Medical Imaging Platforms, and Natural Language Processing Applications.

Based on Application, market is studied across Disease Diagnosis, EHR Management, Patient Monitoring, and Therapeutics. The Disease Diagnosis is further studied across Cancer Detection and Chronic Disease Management. The EHR Management is further studied across Data Encryption & Security and Patient Data Classification. The Patient Monitoring is further studied across Remote Patient Monitoring and Vital Sign Monitoring.

Based on End User, market is studied across Healthcare Insurers, Healthcare Providers, Patients, and Pharmaceutical & Biotech Companies.

Based on Deployment Mode, market is studied across Cloud-Based, Hybrid, and On-Premise. The Cloud-Based is further studied across Private Cloud and Public Cloud.

Geographic Insights Shaping Global Market Dynamics

A review of geographic markets reveals significant regional trends that are shaping the global adoption of AI in healthcare. In the Americas, healthcare institutions are rapidly incorporating AI technologies driven by robust infrastructure, innovative regulatory policies, and high investment in digital transformation. This region has become a hotbed for pioneering research and early adoption of next-generation medical technologies. Europe, the Middle East, and Africa are also notable; many countries in this combined region are investing in AI to tackle unique challenges such as an aging population and the evolving needs of public healthcare services, while also focusing on regulatory frameworks that promote safe adoption. Similarly, in the Asia-Pacific region, dynamic growth is witnessed as technological advancements are intertwined with an increasing demand for quality healthcare services in both urban and rural settings.

Each of these regions faces its own set of opportunities and challenges. The Americas lead in terms of policy support and high investment flows, paving the way for rapid innovation and market expansion. Meanwhile, Europe, the Middle East, and Africa are becoming more agile with emerging AI projects that emphasize personalized and preventive care, while the Asia-Pacific region's vibrant market is driven by high-volume patient bases and expanding digital health ecosystems. These geographic insights not only highlight the diverse market maturity and readiness levels but also indicate how localized strategies can better align product development with regional needs. The competitive dynamics in one area often spark innovations that ripple across borders, reinforcing the interconnected nature of global healthcare markets.

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.

Leading Companies Influencing Technological Advancements

The arena of AI in healthcare is propelled forward by an array of influential companies that are pushing the boundaries of innovation and redefining clinical practices. Among the notable players are firms such as AiCure, LLC and Atomwise Inc., which have carved out distinctive niches in digital health and drug discovery, respectively. Babylon Healthcare Services Ltd and Behold.ai Technologies Limited stand at the forefront of clinical imaging and diagnostic support, while Berg LLC has introduced groundbreaking approaches in biopharmaceutical development. Companies like Butterfly Network, Inc. and ClosedLoop.ai Inc. serve critical roles by developing user-friendly and scalable solutions that address both patient monitoring and operational efficiency.

Another set of industry leaders, including GE Healthcare, Google, LLC by Alphabet, Inc., and Intel Corporation, are redefining the capabilities of hardware and computing power in clinical settings. Meanwhile, International Business Machines Corporation and Koninklijke Philips N.V. have consistently innovated in medical imaging and data analysis, setting industry benchmarks for quality and precision. Medasense Biometrics Ltd. and Microsoft Corporation further contribute to driving secure, robust technological deployments in patient monitoring and health data management. Modernizing Medicine, Inc. is acclaimed for its specialized software solutions, and Nanox Imaging Ltd. represents a new wave of cost-effective imaging technologies.

Additionally, Novo Nordisk A/S, NVIDIA Corporation, Oncora Medical, Oracle Corporation, and Oxipit.ai are pivotal in integrating advanced analytics with clinical diagnostics and improving therapeutic insights. Recursion Pharmaceuticals and Sanofi SA are aggressively harnessing AI to fast-track drug discovery and development processes. Sensely, Inc., Siemens Healthineers AG, and Tempus Labs, Inc. are further complementing this ecosystem with innovative technologies that emphasize precision medicine and optimized patient care. Collectively, these companies not only set high operational standards but also fuel competition that drives continuous improvement and novel solutions for an evolving healthcare environment.

The report delves into recent significant developments in the Artificial Intelligence in Healthcare Market, highlighting leading vendors and their innovative profiles. These include AiCure, LLC, Atomwise Inc., Babylon Healthcare Services Ltd, Behold.ai Technologies Limited, Berg LLC, Butterfly Network, Inc., ClosedLoop.ai Inc., GE Healthcare, Google, LLC by Alphabet, Inc., Intel Corporation, International Business Machines Corporation, Koninklijke Philips N.V., Medasense Biometrics Ltd., Microsoft Corporation, Modernizing Medicine, Inc., Nanox Imaging Ltd., Novo Nordisk A/S, NVIDIA Corporation, Oncora Medical, Oracle Corporation, Oxipit.ai, Recursion Pharmaceuticals, Sanofi SA, Sensely, Inc., Siemens Healthineers AG, and Tempus Labs, Inc.. Strategic Recommendations for Industry Leaders to Capitalize on Emerging Trends

Industry leaders are well-positioned to harness the transformative potential of AI in healthcare by adopting strategies that emphasize innovation, collaboration, and agile adaptation. It is imperative for decision-makers to prioritize investment in robust data infrastructure as a foundational step to capturing valuable insights from large-scale clinical datasets. Capitalizing on emerging trends requires not only funding technological advancements but also engaging in active alliances with research institutions, tech start-ups, and established healthcare providers to facilitate the seamless integration of AI solutions into existing infrastructures.

Leaders must continuously evaluate the regulatory environment and adapt best practices to ensure data privacy, security, and compliance. Embracing flexible deployment modes such as cloud-based and hybrid systems can provide the agility necessary to scale operations efficiently. Equally important is the commitment to staff training and knowledge enhancement: educating clinical teams and operational personnel about the potential and limitations of AI tools ensures that technology complements human expertise rather than replacing it. A proactive approach in fostering an innovation culture can lead to accelerated adoption and a smoother transition into digital-first healthcare models.

Furthermore, strategic investments in research and development will drive continuous innovation and help differentiate service offerings in a competitive market landscape. Closely monitoring market segmentation insights enables leaders to tailor strategies based on application-specific needs, be it in disease diagnosis, patient monitoring, or therapeutics. Finally, leveraging partnerships with leading technology companies can provide early access to cutting-edge solutions and integrate proven methodologies into healthcare systems. These actionable recommendations, when applied collectively, serve to position organizations at the forefront of the AI revolution in healthcare, ensuring sustainable growth and enhanced patient outcomes.

Final Thoughts on the Impact of AI in Healthcare

The revolution spurred by AI in healthcare marks a turning point in the way medical services are delivered and managed across the globe. Through enhanced diagnostic tools, precise patient monitoring systems, and efficient operational frameworks, the integration of AI is not only reshaping clinical practice but also improving overall quality of care. The advancements discussed herein underscore the significant strides made in technology that drive improved patient outcomes, operational efficiency, and ultimately, the promise of personalized medicine.

Reflecting on the transformative shifts witnessed over the recent years, it is evident that AI is more than a transient trend-it is an entrenched component of modern medical practice. The careful segmentation of the market into various dimensions such as technology type, application, end user, and deployment mode has revealed a landscape that is both diverse and robust. Furthermore, the geographic and company analyses provide a comprehensive understanding of how different regions and industry players are converging towards a common goal of revolutionizing patient care.

In summary, healthcare organizations that successfully integrate AI into their operations will not only meet the growing demands of patients but also achieve significant competitive advantages in an increasingly digital world. The journey towards fully realized AI-driven healthcare is laden with challenges, yet the benefits far outweigh the hurdles-ensuring that every stakeholder, from clinicians to policymakers, reaps the rewards of a smarter, more connected ecosystem.

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. Rising prevalence of chronic diseases globally
      • 5.1.1.2. Expanding usage of AI in clinical decision support systems and minimizing diagnostic errors
      • 5.1.1.3. Government initiatives and policies supporting integration of AI in healthcare systems
    • 5.1.2. Restraints
      • 5.1.2.1. Technological limitations in integration of AI tools in healthcare systems
    • 5.1.3. Opportunities
      • 5.1.3.1. Ongoing advancements in AI integrated therapeutic and diagnostic tools
      • 5.1.3.2. Expanding role of AI in personalized medicine and tailored treatment plans
    • 5.1.4. Challenges
      • 5.1.4.1. Data privacy concerns and stringent compliance requirements associated with AI in healthcare
  • 5.2. Market Segmentation Analysis
    • 5.2.1. Type: Increasing preference for software solutions for clinical decision support systems
    • 5.2.2. Application: Expanding application of artificial intelligence in healthcare in disease diagnosis
  • 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 Healthcare Market, by Type

  • 6.1. Introduction
  • 6.2. Hardware
    • 6.2.1. Monitoring Equipment
    • 6.2.2. Robotics
    • 6.2.3. Wearable Devices
  • 6.3. Services
    • 6.3.1. Consulting Services
    • 6.3.2. Deployment & Integration Services
    • 6.3.3. Maintenance & Support
  • 6.4. Software
    • 6.4.1. Clinical Decision Support Systems
    • 6.4.2. Data Management & Analysis
    • 6.4.3. Drug Discovery Platforms
    • 6.4.4. Medical Imaging Platforms
    • 6.4.5. Natural Language Processing Applications

7. Artificial Intelligence in Healthcare Market, by Application

  • 7.1. Introduction
  • 7.2. Disease Diagnosis
    • 7.2.1. Cancer Detection
    • 7.2.2. Chronic Disease Management
  • 7.3. EHR Management
    • 7.3.1. Data Encryption & Security
    • 7.3.2. Patient Data Classification
  • 7.4. Patient Monitoring
    • 7.4.1. Remote Patient Monitoring
    • 7.4.2. Vital Sign Monitoring
  • 7.5. Therapeutics

8. Artificial Intelligence in Healthcare Market, by End User

  • 8.1. Introduction
  • 8.2. Healthcare Insurers
  • 8.3. Healthcare Providers
  • 8.4. Patients
  • 8.5. Pharmaceutical & Biotech Companies

9. Artificial Intelligence in Healthcare Market, by Deployment Mode

  • 9.1. Introduction
  • 9.2. Cloud-Based
    • 9.2.1. Private Cloud
    • 9.2.2. Public Cloud
  • 9.3. Hybrid
  • 9.4. On-Premise

10. Americas Artificial Intelligence in Healthcare Market

  • 10.1. Introduction
  • 10.2. Argentina
  • 10.3. Brazil
  • 10.4. Canada
  • 10.5. Mexico
  • 10.6. United States

11. Asia-Pacific Artificial Intelligence in Healthcare Market

  • 11.1. Introduction
  • 11.2. Australia
  • 11.3. China
  • 11.4. India
  • 11.5. Indonesia
  • 11.6. Japan
  • 11.7. Malaysia
  • 11.8. Philippines
  • 11.9. Singapore
  • 11.10. South Korea
  • 11.11. Taiwan
  • 11.12. Thailand
  • 11.13. Vietnam

12. Europe, Middle East & Africa Artificial Intelligence in Healthcare Market

  • 12.1. Introduction
  • 12.2. Denmark
  • 12.3. Egypt
  • 12.4. Finland
  • 12.5. France
  • 12.6. Germany
  • 12.7. Israel
  • 12.8. Italy
  • 12.9. Netherlands
  • 12.10. Nigeria
  • 12.11. Norway
  • 12.12. Poland
  • 12.13. Qatar
  • 12.14. Russia
  • 12.15. Saudi Arabia
  • 12.16. South Africa
  • 12.17. Spain
  • 12.18. Sweden
  • 12.19. Switzerland
  • 12.20. Turkey
  • 12.21. United Arab Emirates
  • 12.22. United Kingdom

13. Competitive Landscape

  • 13.1. Market Share Analysis, 2024
  • 13.2. FPNV Positioning Matrix, 2024
  • 13.3. Competitive Scenario Analysis
    • 13.3.1. HealthEdge and Codoxo join forces to provide healthcare payers with cutting-edge solutions and services
    • 13.3.2. Google Cloud harnesses AI with DeliverHealth to streamline healthcare documentation and support startups
    • 13.3.3. Microsoft's AI innovations aim to enhance clinicians' workloads and enhance system efficiency
    • 13.3.4. GE HealthCare's strategic acquisition leverages AI innovation to transform ultrasound technology
    • 13.3.5. GE HealthCare Launches AI-Powered Innovations to Shape the Future of Healthcare
    • 13.3.6. HEALWELL AI to Acquire Intrahealth to Create Next Generation AI-powered EHR
    • 13.3.7. HEALWELL AI Completes Acquisition of 'Pentavere,' a Healthcare AI and Data Science Company
  • 13.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. AiCure, LLC
  • 2. Atomwise Inc.
  • 3. Babylon Healthcare Services Ltd
  • 4. Behold.ai Technologies Limited
  • 5. Berg LLC
  • 6. Butterfly Network, Inc.
  • 7. ClosedLoop.ai Inc.
  • 8. GE Healthcare
  • 9. Google, LLC by Alphabet, Inc.
  • 10. Intel Corporation
  • 11. International Business Machines Corporation
  • 12. Koninklijke Philips N.V.
  • 13. Medasense Biometrics Ltd.
  • 14. Microsoft Corporation
  • 15. Modernizing Medicine, Inc.
  • 16. Nanox Imaging Ltd.
  • 17. Novo Nordisk A/S
  • 18. NVIDIA Corporation
  • 19. Oncora Medical
  • 20. Oracle Corporation
  • 21. Oxipit.ai
  • 22. Recursion Pharmaceuticals
  • 23. Sanofi SA
  • 24. Sensely, Inc.
  • 25. Siemens Healthineers AG
  • 26. Tempus Labs, Inc.

LIST OF FIGURES

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

LIST OF TABLES

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