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市場調查報告書
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2021625

2034年醫療保健產業人工智慧市場預測：按交付方式、技術、應用、最終用戶和地區分類的全球分析

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個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球醫療保健領域的 AI 市場規模將達到 300 億美元，並在預測期內以 38.6% 的複合年成長率成長，到 2034 年將達到 4,088 億美元。

人工智慧正透過改進診斷、個人化治療和患者管理來變革醫療保健。先進的演算法能夠處理大量數據，從而實現疾病的早期檢測和個人化護理方案的發展。人工智慧應用有助於分析醫學影像、預測健康結果並最佳化醫院運營，最大限度地減少錯誤和成本。虛擬助理增強了醫病互動和遠端健康監測。此外，人工智慧還能快速辨識有潛力的候選藥物，加速藥物研發和臨床試驗。透過持續創新，人工智慧正使醫療保健更加精準、高效和便捷，重塑患者照護，並推動整個醫療保健服務領域的顯著進步。

根據愛思唯爾發布的《2025年未來臨床醫生》報告，印度超過40%的臨床醫生目前在診療實務中使用人工智慧技術，較去年的12%增加了三倍。這項採用率高於美國（36%）和英國（34%），但低於中國（71%）和亞太地區的平均值（56%）。

對個人化醫療的需求日益成長

對個人化醫療的需求正在推動人工智慧（AI）的應用。先進的演算法可以處理大規模的患者數據，包括基因資訊、生活方式和臨床病史，從而製定個人化的治療方案。這有助於提高治療效果、減少副作用並改善患者的整體預後。人工智慧工具還能實現對患者的持續監測，並根據需求調整治療方法。隨著醫療保健向精準化和個人化解決方案轉型，人工智慧對於開發和提供客製化醫療服務至關重要。這一趨勢圖了以患者為中心的治療策略日益重要，並顯著推動了人工智慧在醫療保健領域的市場擴張。

高昂的實施成本

在醫療保健系統中實施人工智慧需要對技術、基礎設施和專業技術人員進行大量投資。醫院，尤其是在新興經濟體，往往面臨預算限制，阻礙了人工智慧的廣泛應用。模型訓練、系統整合和持續維護的相關成本進一步增加了支出。小規模的醫療機構可能難以承擔如此沉重的經濟負擔，這可能會限制人工智慧的普及。儘管人工智慧有望長期提高效率並改善患者預後，但高昂的初始成本和資源需求仍然是全球醫療保健領域廣泛採用人工智慧技術的主要障礙。

人工智慧驅動的藥物發現開發

人工智慧為藥物研發提供了廣闊的前景，它能夠加速新化合物的發現，並評估其安全性和有效性。先進的演算法可以處理大量的生物和化學數據，顯著降低傳統藥物研發的時間和成本。人工智慧還可以輔助臨床試驗模擬、副作用預測和最佳劑量確定。製藥公司可以利用人工智慧為特定病患小組開發個人化治療方法。隨著對快速、準確且經濟高效的藥物研發需求的日益成長，人工智慧正成為一種變革性工具，在全球範圍內革新藥物研發。

網路安全與資料外洩風險

醫療人工智慧系統極易遭受網路攻擊，因為它們需要處理大量高度敏感的患者資訊。資料外洩可能導致醫療記錄遺失、經濟損失，並損害醫療機構的聲譽。勒索軟體和駭客攻擊等威脅會破壞人工智慧的功能，危及病人安全。確保人工智慧安全需要持續監控、強大的加密技術和嚴格的監管合規，而這些都需要投入大量成本並克服複雜的實施難度。這些網路安全漏洞對醫療人工智慧市場構成重大威脅，因為資料外洩會損害信任、降低採用率，並阻礙醫療服務提供者將人工智慧解決方案全面整合到其臨床工作流程中。

新冠疫情的影響：

新冠疫情顯著加速了人工智慧在醫療保健領域的應用，醫院和診所紛紛尋求快速、數據驅動的解決方案。人工智慧工具被用於病毒檢測、感染傳播預測、患者分診以及最佳化醫療資源緊張情況下的資源分配。機器學習分析了大規模資料集，以預測感染趨勢、識別高風險區域並幫助制定有效的治療方案。遠端醫療和遠端監測激增，人工智慧實現了線上諮詢和持續的患者管理。疫情凸顯了擴充性的智慧醫療解決方案的價值，並推動了全球醫療保健產業對人工智慧技術的投資、接受和整合。

在預測期內，機器學習（ML）細分市場預計將成為規模最大的市場。

由於機器學習 (ML) 能夠處理大規模醫療資料集、識別模式並提供預測性見解，預計在預測期內，ML 細分市場將佔據最大的市場佔有率。 ML 在診斷、個人化醫療、病患風險評估和預測性醫療分析等領域有著廣泛的應用。透過分析患者的歷史和當前訊息，ML 有助於精準地檢測、監測疾病並預測預後。其應用範圍也擴展到醫學影像、藥物研發和臨床操作最佳化。憑藉其適應性強、效率高且結果可衡量等優勢，ML 仍然是領先的細分市場，並在推動全球醫療保健系統中人工智慧技術的成長和應用方面發揮核心作用。

在預測期內，精準醫療（基因組學）領域預計將呈現最高的複合年成長率。

在預測期內，精準醫療（基因組學）領域預計將呈現最高的成長率，這主要得益於其基於基因資訊提供個人化治療的能力。人工智慧透過分析基因組數據、檢測突變並預測患者對治療的反應，從而實現個人化醫療。人們對標靶治療治療日益成長的興趣、基因組學研究的進展以及人工智慧在個人化醫療中的應用，都推動了該領域的快速成長。此外，該領域也將推動藥物研發、預防醫學和疾病早期檢測的發展。

市佔率最大的地區：

在整個預測期內，北美預計將保持最大的市場佔有率，這得益於其先進的醫療基礎設施、數位醫療技術的廣泛應用以及對人工智慧研究的大力投入。該地區受益於許多大型科技和製藥公司的存在，以及政府對推動人工智慧在醫療保健領域的應用的支持。醫療服務提供者對人工智慧的高度認知以及對人工智慧Start-Ups和臨床應用的大量資金投入，正在推動市場成長。北美專注於精準醫療、遠端保健和以數據為中心的醫療解決方案，鞏固了其作為全球人工智慧在醫療保健領域應用最大、最具影響力的市場的地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於快速的數位化進程、不斷擴大的醫療基礎設施以及人工智慧應用的日益普及。政府推行的智慧醫療計畫、對主導Start-Ups的持續投資以及不斷成長的患者需求，都對這一成長起到了推動作用。人工智慧在診斷、遠端醫療、個人化醫療和患者照護等領域的應用正在迅速擴展。由於成本效益高的醫療保健、技術的進步以及臨床醫生和患者意識提升，亞太地區有望成為人工智慧醫療領域成長最快的市場，並成為全球人工智慧解決方案創新和應用的領先中心。

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  • 區域分類
    • 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
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    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球醫療保健領域人工智慧市場：依產品/服務分類

  • 硬體
  • 軟體
  • 服務

第6章：全球醫療保健領域人工智慧市場：按技術分類

  • 機器學習（ML）
  • 自然語言處理（NLP）
  • 電腦視覺

第7章：全球醫療保健領域人工智慧市場：按應用領域分類

  • 診斷
  • 精準醫療（基因體學）
  • 藥物發現與開發
  • 病患監測和護理
  • 最佳化醫療操作

第8章：全球醫療保健產業人工智慧市場：按最終用戶分類

  • 醫院和診所
  • 製藥和生物技術公司
  • 學術研究機構
  • 保險公司和居家醫療提供者

第9章：全球醫療保健領域人工智慧市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第10章 戰略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第11章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第12章：公司簡介

  • 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.