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市场调查报告书
商品编码
2021625

2034年医疗保健产业人工智慧市场预测：按交付方式、技术、应用、最终用户和地区分類的全球分析

AI in Healthcare Market Forecasts to 2034 - Global Analysis By Offering (Hardware, Software and Services), Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，预计到 2026 年，全球医疗保健领域的 AI 市场规模将达到 300 亿美元，并在预测期内以 38.6% 的复合年增长率增长，到 2034 年将达到 4,088 亿美元。

人工智慧正透过改进诊断、个人化治疗和患者管理来变革医疗保健。先进的演算法能够处理大量数据，从而实现疾病的早期检测和个人化护理方案的发展。人工智慧应用有助于分析医学影像、预测健康结果并优化医院运营，最大限度地减少错误和成本。虚拟助理增强了医病互动和远端健康监测。此外，人工智慧还能快速辨识有潜力的候选药物，加速药物研发和临床试验。透过持续创新，人工智慧正使医疗保健更加精准、高效和便捷，重塑患者照护，并推动整个医疗保健服务领域的显着进步。

根据爱思唯尔发布的《2025年未来临床医生》报告，印度超过40%的临床医生目前在诊疗实务中使用人工智慧技术，较去年的12%增加了三倍。这项采用率高于美国（36%）和英国（34%），但低于中国（71%）和亚太地区的平均值（56%）。

对个人化医疗的需求日益增长

对个人化医疗的需求正在推动人工智慧（AI）的应用。先进的演算法可以处理大规模的患者数据，包括基因资讯、生活方式和临床病史，从而製定个人化的治疗方案。这有助于提高治疗效果、减少副作用并改善患者的整体预后。人工智慧工具还能实现对患者的持续监测，并根据需求调整治疗方法。随着医疗保健向精准化和个人化解决方案转型，人工智慧对于开发和提供客製化医疗服务至关重要。这一趋势图了以患者为中心的治疗策略日益重要，并显着推动了人工智慧在医疗保健领域的市场扩张。

高昂的实施成本

在医疗保健系统中实施人工智慧需要对技术、基础设施和专业技术人员进行大量投资。医院，尤其是在新兴经济体，往往面临预算限制，阻碍了人工智慧的广泛应用。模型训练、系统整合和持续维护的相关成本进一步增加了支出。小规模的医疗机构可能难以承担如此沉重的经济负担，这可能会限制人工智慧的普及。儘管人工智慧有望长期提高效率并改善患者预后，但高昂的初始成本和资源需求仍然是全球医疗保健领域广泛采用人工智慧技术的主要障碍。

人工智慧驱动的药物发现开发

人工智慧为药物研发提供了广阔的前景，它能够加速新化合物的发现，并评估其安全性和有效性。先进的演算法可以处理大量的生物和化学数据，显着降低传统药物研发的时间和成本。人工智慧还可以辅助临床试验模拟、副作用预测和最佳剂量确定。製药公司可以利用人工智慧为特定病患小组开发个人化治疗方法。随着对快速、准确且经济高效的药物研发需求的日益增长，人工智慧正成为一种变革性工具，在全球范围内革新药物研发。

网路安全与资料外洩风险

医疗人工智慧系统极易遭受网路攻击，因为它们需要处理大量高度敏感的患者资讯。资料外洩可能导致医疗记录遗失、经济损失，并损害医疗机构的声誉。勒索软体和骇客攻击等威胁会破坏人工智慧的功能，危及病人安全。确保人工智慧安全需要持续监控、强大的加密技术和严格的监管合规，而这些都需要投入大量成本并克服复杂的实施难度。这些网路安全漏洞对医疗人工智慧市场构成重大威胁，因为资料外洩会损害信任、降低采用率，并阻碍医疗服务提供者将人工智慧解决方案全面整合到其临床工作流程中。

新冠疫情的影响：

新冠疫情显着加速了人工智慧在医疗保健领域的应用，医院和诊所纷纷寻求快速、数据驱动的解决方案。人工智慧工具被用于病毒检测、感染传播预测、患者分诊以及优化医疗资源紧张情况下的资源分配。机器学习分析了大规模资料集，以预测感染趋势、识别高风险区域并帮助制定有效的治疗方案。远端医疗和远端监测激增，人工智慧实现了线上咨询和持续的患者管理。疫情凸显了扩充性的智慧医疗解决方案的价值，并推动了全球医疗保健产业对人工智慧技术的投资、接受和整合。

在预测期内，机器学习（ML）细分市场预计将成为规模最大的市场。

由于机器学习 (ML) 能够处理大规模医疗资料集、识别模式并提供预测性见解，预计在预测期内，ML 细分市场将占据最大的市场份额。 ML 在诊断、个人化医疗、病患风险评估和预测性医疗分析等领域有着广泛的应用。透过分析患者的历史和当前讯息，ML 有助于精准地检测、监测疾病并预测预后。其应用范围也扩展到医学影像、药物研发和临床操作优化。凭藉其适应性强、效率高且结果可衡量等优势，ML 仍然是领先的细分市场，并在推动全球医疗保健系统中人工智慧技术的成长和应用方面发挥核心作用。

在预测期内，精准医疗（基因组学）领域预计将呈现最高的复合年增长率。

在预测期内，精准医疗（基因组学）领域预计将呈现最高的成长率，这主要得益于其基于基因资讯提供个人化治疗的能力。人工智慧透过分析基因组数据、检测突变并预测患者对治疗的反应，从而实现个人化医疗。人们对标靶治疗治疗日益增长的兴趣、基因组学研究的进展以及人工智慧在个人化医疗中的应用，都推动了该领域的快速成长。此外，该领域也将推动药物研发、预防医学和疾病早期检测的发展。

市占率最大的地区：

在整个预测期内，北美预计将保持最大的市场份额，这得益于其先进的医疗基础设施、数位医疗技术的广泛应用以及对人工智慧研究的大力投入。该地区受益于许多大型科技和製药公司的存在，以及政府对推动人工智慧在医疗保健领域的应用的支持。医疗服务提供者对人工智慧的高度认知以及对人工智慧Start-Ups和临床应用的大量资金投入，正在推动市场成长。北美专注于精准医疗、远端保健和以数据为中心的医疗解决方案，巩固了其作为全球人工智慧在医疗保健领域应用最大、最具影响力的市场的地位。

复合年增长率最高的地区：

在预测期内，亚太地区预计将呈现最高的复合年增长率，这主要得益于快速的数位化进程、不断扩大的医疗基础设施以及人工智慧应用的日益普及。政府推行的智慧医疗计画、对主导Start-Ups的持续投资以及不断增长的患者需求，都对这一增长起到了推动作用。人工智慧在诊断、远端医疗、个人化医疗和患者照护等领域的应用正在迅速扩展。由于成本效益高的医疗保健、技术的进步以及临床医生和患者意识提升，亚太地区有望成为人工智慧医疗领域成长最快的市场，并成为全球人工智慧解决方案创新和应用的领先中心。

免费客製化服务：

所有购买此报告的客户均可享受以下免费自订选项之一：

  • 企业概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域划分
    • 应客户要求，我们提供主要国家和地区的市场估算和预测，以及复合年增长率（註：需进行可行性检查）。
  • 竞争性标竿分析
    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章执行摘要

  • 市场概览及主要亮点
  • 驱动因素、挑战与机会
  • 竞争格局概述
  • 战略洞察与建议

第二章：研究框架

  • 研究目标和范围
  • 相关人员分析
  • 研究假设和限制
  • 调查方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 技术与创新展望
  • 新兴市场/高成长市场
  • 监管和政策环境
  • 新冠疫情的影响及復苏前景

第四章：竞争环境与策略评估

  • 波特五力分析
    • 供应商的议价能力
    • 买方的议价能力
    • 替代品的威胁
    • 新进入者的威胁
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球医疗保健领域人工智慧市场：依产品/服务分类

  • 硬体
  • 软体
  • 服务

第六章：全球医疗保健领域人工智慧市场：按技术划分

  • 机器学习（ML）
  • 自然语言处理（NLP）
  • 电脑视觉

第七章：全球医疗保健领域人工智慧市场：按应用领域划分

  • 诊断
  • 精准医疗（基因体学）
  • 药物发现与开发
  • 病患监测和护理
  • 优化医疗操作

第八章：全球医疗保健产业人工智慧市场：按最终用户划分

  • 医院和诊所
  • 製药和生物技术公司
  • 学术研究机构
  • 保险公司和居家医疗提供者

第九章：全球医疗保健领域人工智慧市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第十章 战略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十一章 产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟和合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十二章：公司简介

  • Aidoc
  • Tempus
  • Teladoc Health
  • GE Healthcare
  • Siemens Healthineers
  • Philips Healthcare
  • Google
  • NVIDIA
  • Medtronic
  • IBM
  • Microsoft
  • Oracle
  • Epic Systems
  • K Health
  • Owkin
  • PathAI
  • Abridge
  • Butterfly Network
Product Code: SMRC34965

According to Stratistics MRC, the Global AI in Healthcare Market is accounted for $30.0 billion in 2026 and is expected to reach $408.8 billion by 2034 growing at a CAGR of 38.6% during the forecast period. AI is transforming healthcare by improving diagnosis, personalized treatments, and patient management. Advanced algorithms process large datasets, enabling early disease detection and tailored care plans. AI applications support medical imaging analysis, predict health outcomes, and optimize hospital operations, minimizing mistakes and expenses. Virtual assistants enhance patient interaction and remote health monitoring. Additionally, AI speeds up drug development and clinical trials by quickly identifying promising candidates. With continuous innovation, AI ensures healthcare becomes more precise, efficient, and widely accessible, reshaping the patient care landscape and driving significant improvements in overall medical services.

According to Elsevier's Clinician of the Future 2025 report, over 40% of clinicians in India are now using AI technologies in their practice-a three-fold increase from 12% last year. This adoption rate is higher than the United States (36%) and the United Kingdom (34%), though lower than China (71%) and the Asia-Pacific average (56%).

Market Dynamics:

Driver:

Rising demand for personalized medicine

The demand for personalized healthcare is driving AI adoption, as advanced algorithms can process large-scale patient data-including genetics, lifestyle, and clinical history-to create individualized treatment plans. This ensures higher treatment effectiveness, fewer side effects, and better overall patient outcomes. AI tools also allow continuous monitoring of patients, enabling adjustments to therapies as needed. As healthcare shifts toward precision and tailored solutions, AI becomes essential for developing and delivering customized care. This trend significantly contributes to the expansion of the AI in healthcare market, reflecting the increasing importance of patient-specific treatment strategies.

Restraint:

High implementation costs

Introducing AI into healthcare systems requires substantial investment in technology, infrastructure, and skilled professionals. Hospitals, particularly in emerging economies, often encounter budget limitations that hinder broad adoption. Expenses related to model training, system integration, and continuous maintenance further increase costs. Smaller healthcare facilities may find it difficult to justify such financial commitments, limiting AI deployment. Although AI promises long-term efficiency and improved patient outcomes, the high initial expenditure and resource demands continue to act as major obstacles, restraining the widespread utilization of AI technologies in healthcare settings worldwide.

Opportunity:

Development of AI-powered drug discovery

AI presents a promising opportunity in drug discovery, expediting the detection of new compounds and assessing their safety and effectiveness. Advanced algorithms can process extensive biological and chemical data, significantly cutting the time and expense of traditional drug development. AI also aids in simulating clinical trials, predicting adverse effects, and determining optimal dosages. Pharmaceutical firms can utilize AI to create personalized therapies for specific patient groups. As the need for rapid, precise, and cost-efficient drug development increases, AI emerges as a transformative tool in revolutionizing pharmaceutical research and development on a global scale.

Threat:

Cyber security and data breach risks

Healthcare AI systems process large amounts of confidential patient information, making them vulnerable to cyberattacks. Data breaches can expose medical records, cause financial damage, and harm institutional reputation. Threats like ransomware or hacking can disrupt AI functionality and risk patient safety. Ensuring AI security demands continuous monitoring, strong encryption, and strict regulatory compliance, which are both costly and complex. These cybersecurity vulnerabilities represent a major threat to the AI in healthcare market, as compromised data can erode trust, reduce adoption rates, and deter healthcare providers from fully integrating AI solutions into clinical workflows.

Covid-19 Impact:

The COVID-19 outbreak greatly accelerated AI adoption in healthcare, as hospitals and clinics sought rapid, data-driven solutions. AI tools were used for virus detection, predicting outbreaks, patient triage, and optimizing resource allocation in strained healthcare systems. Machine learning analyzed large datasets to forecast infection trends, identify high-risk areas, and support effective treatment planning. Telehealth and remote monitoring surged, with AI enabling virtual consultations and continuous patient management. The pandemic emphasized the value of scalable and intelligent healthcare solutions, acting as a catalyst that increased investment, acceptance, and integration of AI technologies across the global healthcare sector.

The machine learning (ML) segment is expected to be the largest during the forecast period

The machine learning (ML) segment is expected to account for the largest market share during the forecast period because it can process large healthcare datasets, identify patterns, and provide predictive insights. ML is extensively applied in diagnostics, personalized treatments, patient risk evaluations, and predictive healthcare analytics. By analyzing historical and current patient information, ML supports precise disease detection, monitoring, and outcome forecasting. Its use extends to medical imaging, drug development, and optimizing clinical operations. Due to its adaptability, efficiency, and measurable results, ML remains the leading segment, playing a central role in driving the growth and implementation of AI technologies across healthcare systems globally.

The precision medicine (genomics) segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the precision medicine (genomics) segment is predicted to witness the highest growth rate, driven by its ability to provide personalized therapies based on genetic information. AI analyzes genomic data, detects mutations, and predicts how patients will respond to treatments, allowing tailored care. Increasing interest in targeted therapies, advances in genomics research, and AI integration in personalized medicine contribute to its rapid growth. This segment also enhances drug development, preventive care, and early detection of diseases.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, owing to its advanced medical infrastructure, widespread adoption of digital health technologies, and strong investment in AI research. The region benefits from the presence of leading tech and pharmaceutical firms, as well as government support promoting AI in healthcare. High provider awareness and substantial funding for AI-driven startups and clinical applications drive growth. With emphasis on precision medicine, telehealth, and data-centric healthcare solutions, North America maintains its position as the largest and most influential market for AI adoption in healthcare worldwide.

Region with highest CAGR:

Over the forecast period, the Asia-Pacific region is anticipated to exhibit the highest CAGR, fueled by rapid digitalization, expanding healthcare infrastructure, and increased AI adoption. Government programs promoting intelligent healthcare, rising investments in AI-driven startups, and growing patient demand contribute to this growth. AI applications across diagnostics, telehealth, personalized medicine, and patient care are quickly expanding. The region benefits from cost-efficient healthcare, technological progress and greater awareness among clinicians and patients, making Asia-Pacific the highest growth rate market in AI healthcare and a key hub for innovation and adoption of AI solutions globally.

Key players in the market

Some of the key players in AI in Healthcare Market include Aidoc, Tempus, Teladoc Health, GE Healthcare, Siemens Healthineers, Philips Healthcare, Google, NVIDIA, Medtronic, IBM, Microsoft, Oracle, Epic Systems, K Health, Owkin, PathAI, Abridge and Butterfly Network.

Key Developments:

In January 2026, Microsoft Corp has been awarded a $170,444,462 firm-fixed-price task order for the Cloud One Program by the U.S. Department of War. The contract will provide Microsoft Azure cloud service offerings to support the Air Force's Cloud One Program and its customers. Work on the project will be performed at Microsoft's designated facilities across the contiguous United States.

In February 2026, Medtronic has agreed to acquire CathWorks, an Israeli medtech company focused on the diagnosis and treatment of coronary artery disease, for up to $585 million. CathWorks is known for its FFRangio technology, which uses advanced artificial intelligence (AI) algorithms and computational science to obtain fractional flow reserve (FFR) measurements of the coronary tree from routine X-ray images.

In December 2025, IBM and Confluent, Inc. announced they have entered into a definitive agreement under which IBM will acquire all of the issued and outstanding common shares of Confluent for $31 per share, representing an enterprise value of $11 billion. Confluent provides a leading open-source enterprise data streaming platform that connects processes and governs reusable and reliable data and events in real time, foundational for the deployment of AI.

Offerings Covered:

  • Hardware
  • Software
  • Services

Technologies Covered:

  • Machine Learning (ML)
  • Natural Language Processing (NLP)
  • Computer Vision

Applications Covered:

  • Diagnostics
  • Precision Medicine (Genomics)
  • Drug Discovery & Development
  • Patient Monitoring & Care
  • Healthcare Operations Optimization

End Users Covered:

  • Hospitals & Clinics
  • Pharmaceutical & Biotechnology Companies
  • Academic & Research Institutes
  • Insurance & Home Healthcare Providers

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI in Healthcare Market, By Offering

  • 5.1 Hardware
  • 5.2 Software
  • 5.3 Services

6 Global AI in Healthcare Market, By Technology

  • 6.1 Machine Learning (ML)
  • 6.2 Natural Language Processing (NLP)
  • 6.3 Computer Vision

7 Global AI in Healthcare Market, By Application

  • 7.1 Diagnostics
  • 7.2 Precision Medicine (Genomics)
  • 7.3 Drug Discovery & Development
  • 7.4 Patient Monitoring & Care
  • 7.5 Healthcare Operations Optimization

8 Global AI in Healthcare Market, By End User

  • 8.1 Hospitals & Clinics
  • 8.2 Pharmaceutical & Biotechnology Companies
  • 8.3 Academic & Research Institutes
  • 8.4 Insurance & Home Healthcare Providers

9 Global AI in Healthcare Market, By Geography

  • 9.1 North America
    • 9.1.1 United States
    • 9.1.2 Canada
    • 9.1.3 Mexico
  • 9.2 Europe
    • 9.2.1 United Kingdom
    • 9.2.2 Germany
    • 9.2.3 France
    • 9.2.4 Italy
    • 9.2.5 Spain
    • 9.2.6 Netherlands
    • 9.2.7 Belgium
    • 9.2.8 Sweden
    • 9.2.9 Switzerland
    • 9.2.10 Poland
    • 9.2.11 Rest of Europe
  • 9.3 Asia Pacific
    • 9.3.1 China
    • 9.3.2 Japan
    • 9.3.3 India
    • 9.3.4 South Korea
    • 9.3.5 Australia
    • 9.3.6 Indonesia
    • 9.3.7 Thailand
    • 9.3.8 Malaysia
    • 9.3.9 Singapore
    • 9.3.10 Vietnam
    • 9.3.11 Rest of Asia Pacific
  • 9.4 South America
    • 9.4.1 Brazil
    • 9.4.2 Argentina
    • 9.4.3 Colombia
    • 9.4.4 Chile
    • 9.4.5 Peru
    • 9.4.6 Rest of South America
  • 9.5 Rest of the World (RoW)
    • 9.5.1 Middle East
      • 9.5.1.1 Saudi Arabia
      • 9.5.1.2 United Arab Emirates
      • 9.5.1.3 Qatar
      • 9.5.1.4 Israel
      • 9.5.1.5 Rest of Middle East
    • 9.5.2 Africa
      • 9.5.2.1 South Africa
      • 9.5.2.2 Egypt
      • 9.5.2.3 Morocco
      • 9.5.2.4 Rest of Africa

10 Strategic Market Intelligence

  • 10.1 Industry Value Network and Supply Chain Assessment
  • 10.2 White-Space and Opportunity Mapping
  • 10.3 Product Evolution and Market Life Cycle Analysis
  • 10.4 Channel, Distributor, and Go-to-Market Assessment

11 Industry Developments and Strategic Initiatives

  • 11.1 Mergers and Acquisitions
  • 11.2 Partnerships, Alliances, and Joint Ventures
  • 11.3 New Product Launches and Certifications
  • 11.4 Capacity Expansion and Investments
  • 11.5 Other Strategic Initiatives

12 Company Profiles

  • 12.1 Aidoc
  • 12.2 Tempus
  • 12.3 Teladoc Health
  • 12.4 GE Healthcare
  • 12.5 Siemens Healthineers
  • 12.6 Philips Healthcare
  • 12.7 Google
  • 12.8 NVIDIA
  • 12.9 Medtronic
  • 12.10 IBM
  • 12.11 Microsoft
  • 12.12 Oracle
  • 12.13 Epic Systems
  • 12.14 K Health
  • 12.15 Owkin
  • 12.16 PathAI
  • 12.17 Abridge
  • 12.18 Butterfly Network

List of Tables

  • Table 1 Global AI in Healthcare Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI in Healthcare Market Outlook, By Offering (2023-2034) ($MN)
  • Table 3 Global AI in Healthcare Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI in Healthcare Market Outlook, By Software (2023-2034) ($MN)
  • Table 5 Global AI in Healthcare Market Outlook, By Services (2023-2034) ($MN)
  • Table 6 Global AI in Healthcare Market Outlook, By Technology (2023-2034) ($MN)
  • Table 7 Global AI in Healthcare Market Outlook, By Machine Learning (ML) (2023-2034) ($MN)
  • Table 8 Global AI in Healthcare Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 9 Global AI in Healthcare Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 10 Global AI in Healthcare Market Outlook, By Application (2023-2034) ($MN)
  • Table 11 Global AI in Healthcare Market Outlook, By Diagnostics (2023-2034) ($MN)
  • Table 12 Global AI in Healthcare Market Outlook, By Precision Medicine (Genomics) (2023-2034) ($MN)
  • Table 13 Global AI in Healthcare Market Outlook, By Drug Discovery & Development (2023-2034) ($MN)
  • Table 14 Global AI in Healthcare Market Outlook, By Patient Monitoring & Care (2023-2034) ($MN)
  • Table 15 Global AI in Healthcare Market Outlook, By Healthcare Operations Optimization (2023-2034) ($MN)
  • Table 16 Global AI in Healthcare Market Outlook, By End User (2023-2034) ($MN)
  • Table 17 Global AI in Healthcare Market Outlook, By Hospitals & Clinics (2023-2034) ($MN)
  • Table 18 Global AI in Healthcare Market Outlook, By Pharmaceutical & Biotechnology Companies (2023-2034) ($MN)
  • Table 19 Global AI in Healthcare Market Outlook, By Academic & Research Institutes (2023-2034) ($MN)
  • Table 20 Global AI in Healthcare Market Outlook, By Insurance & Home Healthcare Providers (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.