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市場調查報告書
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2045966

醫療保健領域人工智慧市場－全球產業規模、佔有率、趨勢、機會、預測：產品、技術、應用、最終用戶、區域及競爭格局（2021-2031）

AI in Healthcare Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Offering, By Technology, By Application, By End User By Region & Competition, 2021-2031F
出版日期: | 出版商: TechSci Research | 英文 185 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球醫療保健領域的人工智慧市場預計將從 2025 年的 360.2 億美元大幅成長至 2031 年的 2,500.8 億美元，複合年成長率將達到 38.12%。

人工智慧在醫療領域的應用，利用機器學習、自然語言處理和其他認知技術來分析醫療數據，從而輔助診斷、最佳化治療方案並簡化行政工作。這個市場顯著成長的主要促進因素包括：日益成長且複雜度不斷增加的醫療數據量、降低營運成本的迫切需求，以及需要持續管理的慢性病在全球發病率的上升。這些核心要素為將計算智慧融入臨床流程、改善決策和患者預後奠定了堅實的基礎。

市場概覽
預測期 2027-2031
市場規模：2025年 360.2億美元
市場規模：2031年 2500.8億美元
複合年成長率：2026-2031年 38.12%
成長最快的細分市場 藥物發現
最大的市場 北美洲

根據美國醫學會 (AMA) 的數據，到 2024 年，66% 的醫生將在臨床實踐中使用人工智慧 (AI)，這表明人工智慧的普及率將顯著提高。然而，數據互通性不足以及對患者數據隱私的持續擔憂是市場進一步擴張的主要障礙。醫療資訊系統的碎片化導致資料孤島，阻礙了無縫資訊交換，而無縫資訊交流對於訓練高級演算法以及在不同的醫療環境中實施擴充性的人工智慧解決方案至關重要。

市場促進因素

人工智慧在醫療保健領域的市場主要促進因素是全球醫療專業人員短缺和臨床醫生普遍存在的職業倦怠問題。醫療系統正在積極尋求自動化解決方案，以應對患者需求與現有醫護人員之間日益擴大的差距。這種結構性短缺使得利用智慧系統增強人類能力（特別是透過減輕行政負擔和最佳化診斷流程）變得至關重要。例如，飛利浦於2025年5月發布的《2025年未來健康指數》報告預測，到2030年，全球將出現1,100萬醫療專業人員的缺口，凸顯了技術干預的緊迫性。因此，醫療服務提供者正迅速採用人工智慧工具來維持照護標準，而愛思唯爾於2025年7月發布的《2025年未來臨床醫生》報告也支持了這一趨勢。報告顯示，48%的臨床醫生已經在工作中使用人工智慧工具。

此外，人工智慧在藥物發現和藥物開發領域的加速應用，正透過變革藥物研發流程，大幅推動市場擴張。傳統的藥物發現方法往往失敗率高、研發週期長，而生成式演算法能夠更有效率地辨識有前景的候選藥物，正逐漸取代這些方法。這種模式轉移將促使企業對運算平台進行大量投資，進而降低新療法上市所需的資本支出。該應用的戰略意義顯而易見。根據出版報告《醫療保健和生命科學領域的人工智慧現狀：2025年趨勢》，62%的受訪製藥和生物技術公司表示，藥物發現是生成式人工智慧的主要應用領域。

市場挑戰

全球醫療人工智慧市場成長的主要障礙在於資料互通性不足以及對病患​​資料隱私的持續擔憂。人工智慧模型依賴廣泛、多樣化且相互關聯的資料集，以產生準確的臨床見解，並確保不同病患小組獲得有效的治療效果。然而，當前的醫療保健環境的特徵是資訊系統碎片化，關鍵的醫療記錄被孤立地儲存在各個系統中。這種碎片化的基礎設施阻礙了訓練強大演算法所需資料的順利收集，從而限制了人工智慧解決方案的擴充性，並降低了其在各種臨床環境中部署時的可靠性。

這些營運效率低下的問題因對高度敏感的健康資訊安全的嚴重擔憂而加劇，這往往導致嚴格的資料管治政策制定。這種謹慎態度減緩了創新步伐，因為機構通常優先考慮風險規避而非採用新技術。醫療保健資訊與管理系統協會 (HIMSS) 在 2024 年報告中指出，72% 的醫療保健專業人員將資料隱私列為人工智慧應用的首要擔憂。這種普遍存在的擔憂阻礙了市場擴張，因為它使合規工作更加複雜，並減緩了具有潛在變革意義的運算工具的採用速度。

市場趨勢

一個值得關注的趨勢是將生成式人工智慧引入臨床記錄。這從根本上改變了醫療服務提供者的工作流程，使其從手動資料輸入轉變為基於環境聲音的聆聽和自動記錄。這種方法是在病房內引入自然語言處理工具，即時記錄診療過程。這使得醫生無需專注於電腦螢幕，即可與患者保持直接互動並建立信任。醫療機構正在積極採用這些解決方案，以提高記錄的準確性並減輕電子健康記錄帶來的認知負擔。根據斯科茨代爾研究中心於2025年5月開展的一項關於人工智慧在醫療保健領域應用情況的調查，53%的醫療機構報告稱，人工智慧在臨床記錄中的應用取得了很高的成功率，這表明這項技術正在迅速超越最初的試點階段。

另一個重要趨勢是自主代理人工智慧的興起。這標誌著醫療機構內部的人工智慧從被動分析轉向主動任務執行的轉變。與傳統的聊天機器人不同，這些自主代理無需人工干預即可執行複雜的多階段任務，例如安排預約、處理保險索賠以及優先處理患者諮詢。這種向基於代理的工作流程的轉變使醫療機構能夠在保持高水準患者服務的同時，高效地擴展營運規模。這項技術的戰略重要性正日益受到認可。根據Google雲端2025年10月發布的出版報告《人工智慧在醫療保健和生命科學領域的投資回報率》，34%的醫療機構高層表示，技術支援和病患體驗是自主人工智慧代理的主要應用領域，這凸顯了它們在自動化核心業務功能方面日益重要的作用。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：全球醫療保健人工智慧市場展望

  • 市場規模及預測
    • 按金額
  • 市佔率及預測
    • 依交付方式（軟體與硬體）分類
    • 透過科技（機器學習、電腦視覺、自然語言處理、情境感知計算）
    • 按應用領域（醫學影像與診斷、機器人手術、藥物研發、住院治療與醫院管理、病患資料與風險分析等）
    • 按最終用戶（醫療保健提供者、製藥和生物技術公司、患者、其他）分類
    • 按地區
    • 按公司（2025 年）
  • 市場地圖

第6章：北美醫療保健人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 北美洲：國別分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：人工智慧在歐洲醫療保健領域的市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 歐洲：國別分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太地區醫療保健領域人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 亞太地區：國別分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東和非洲醫療保健領域人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 中東與非洲：國別分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：南美醫療保健領域人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 南美洲：國別分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第11章 市場動態

  • 促進因素
  • 任務

第12章 市場趨勢與發展

  • 併購
  • 產品發布
  • 近期趨勢

第13章：全球醫療保健人工智慧市場：SWOT分析

第14章：波特五力分析

  • 產業競爭
  • 新進入者的潛力
  • 供應商的議價能力
  • 顧客權力
  • 替代品的威脅

第15章 競爭格局

  • Google Health/DeepMind
  • Tempus AI
  • GE Healthcare
  • Siemens Healthineers
  • Philips Healthcare
  • Teladoc Health
  • Aidoc
  • PathAI
  • Butterfly Network
  • Arterys

第16章 策略建議

第17章：關於研究公司及免責聲明

簡介目錄
Product Code: 10647

The global AI in healthcare market is projected to expand significantly, rising from USD 36.02 billion in 2025 to USD 250.08 billion by 2031, demonstrating a compound annual growth rate of 38.12%. Artificial intelligence in healthcare involves leveraging machine learning, natural language processing, and other cognitive technologies to analyze medical data, thereby assisting in diagnosis, optimizing treatment plans, and improving administrative efficiencies. This substantial market growth is fundamentally propelled by the escalating volume of intricate healthcare data, the urgent necessity to curtail operational expenditures, and the increasing worldwide incidence of chronic diseases demanding ongoing oversight. These core elements establish a robust foundation for integrating computational intelligence into clinical processes to enhance decision-making and patient outcomes.

Market Overview
Forecast Period2027-2031
Market Size 2025USD 36.02 Billion
Market Size 2031USD 250.08 Billion
CAGR 2026-203138.12%
Fastest Growing SegmentDrug Discovery
Largest MarketNorth America

In 2024, a notable 66% of physicians reported utilizing artificial intelligence in their practice, according to the American Medical Association, indicating a considerable increase in adoption. However, a significant obstacle to further market expansion stems from inadequate data interoperability and ongoing concerns surrounding patient data privacy. The fragmented nature of health information systems leads to data silos, which impede the seamless exchange of information essential for training sophisticated algorithms and implementing scalable AI solutions across varied healthcare environments.

Market Driver

A primary driver fueling the AI in healthcare market is the global shortage of healthcare professionals and the pervasive issue of clinician burnout. Health systems are actively seeking automated solutions to address the growing disparity between patient demand and available workforce capacity. This structural deficit necessitates the use of intelligent systems to enhance human capabilities, particularly by alleviating administrative responsibilities and optimizing diagnostic processes. For instance, Philips' 'Future Health Index 2025' report, May 2025, forecasts a critical shortfall of 11 million health workers by 2030, underscoring the urgent need for technological intervention. As a result, healthcare providers are quickly incorporating AI tools to uphold care standards, a trend further supported by Elsevier's 'Clinician of the Future 2025' report, July 2025, which indicates that 48% of clinicians have already employed an artificial intelligence tool in their professional work.

Furthermore, the accelerated adoption of AI for drug discovery and development significantly contributes to market expansion by transforming the pharmaceutical research pipeline. Traditional approaches, often marked by high failure rates and extended timelines, are increasingly being replaced by generative algorithms that can identify promising drug candidates with greater efficiency. This paradigm shift encourages substantial investment in computational platforms, which in turn reduces the capital investment required to introduce new therapeutics to the market. The strategic importance of this application is clear; according to NVIDIA's 'State of AI in Healthcare and Life Sciences: 2025 Trends' report, March 2025, 62% of pharmaceutical and biotechnology company respondents identified drug discovery as their leading generative AI application.

Market Challenge

A significant impediment to the growth of the global AI in healthcare market is the lack of data interoperability, coupled with ongoing concerns about patient data privacy. Artificial intelligence models depend on extensive, varied, and interconnected datasets to generate precise clinical insights and ensure effective outcomes across diverse patient groups. Nevertheless, the prevailing healthcare environment is characterized by disjointed information systems that confine vital medical records within isolated silos. This fragmented infrastructure obstructs the effortless collection of data essential for training resilient algorithms, consequently limiting the scalability of AI solutions and diminishing their dependability when deployed in various clinical environments.

These operational inefficiencies are exacerbated by considerable worries regarding the security of sensitive health information, which often results in stringent data governance policies. Such caution slows the rate of innovation as organizations frequently prioritize mitigating risks over integrating new technologies. The Healthcare Information and Management Systems Society reported in 2024 that 72% of healthcare professionals viewed data privacy as a major concern regarding AI adoption. This prevalent apprehension hinders market expansion by complicating compliance efforts and delaying the implementation of potentially transformative computational tools.

Market Trends

A significant trend observed is the adoption of generative AI for clinical documentation, which is fundamentally transforming provider workflows by shifting from manual data entry to ambient listening and automated note creation. This approach involves deploying natural language processing tools within patient rooms to record consultations in real-time, allowing physicians to maintain direct engagement and rapport with patients instead of focusing on computer screens. Healthcare systems are actively integrating these solutions to enhance documentation accuracy and reduce the cognitive burden associated with electronic health records. The Scottsdale Institute's 'Adoption of Artificial Intelligence in Healthcare' survey, May 2025, indicated that 53% of health systems reported high success with AI in clinical documentation, suggesting this technology is quickly moving beyond initial pilot phases.

Another critical trend is the emergence of autonomous agentic AI, which signifies an evolution from merely passive analysis to proactive operational execution within healthcare organizations. In contrast to conventional chatbots, these independent agents are capable of performing intricate, multi-step tasks such as scheduling appointments, processing claims, and triaging patient inquiries without requiring human intervention. This move towards agentic workflows empowers institutions to efficiently scale their operations while upholding high service standards for patients. The strategic importance of this technology is increasingly acknowledged; Google Cloud's 'The ROI of AI in Healthcare and Life Sciences' report, October 2025, found that 34% of healthcare executives identified technical support and patient experience as the primary applications for autonomous AI agents, emphasizing their expanding role in automating core business functions.

Key Market Players

  • Google Health / DeepMind
  • Tempus AI
  • GE Healthcare
  • Siemens Healthineers
  • Philips Healthcare
  • Teladoc Health
  • Aidoc
  • PathAI
  • Butterfly Network
  • Arterys

Report Scope

In this report, the Global AI in Healthcare Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

AI in Healthcare Market, By Offering

  • Software
  • Hardware

AI in Healthcare Market, By Technology

  • Machine Learning
  • Computer Vision
  • Natural Language Processing
  • Context-Aware Computing

AI in Healthcare Market, By Application

  • Medical Imaging & Diagnostics
  • Robotic Surgeries
  • Drug Discovery
  • Inpatient Care & Hospital Management
  • Patient Data & Risk Analysis
  • Others

AI in Healthcare Market, By End User

  • Healthcare Providers
  • Pharmaceutical & Biotechnology Companies
  • Patients
  • Others

AI in Healthcare Market, By Region

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • France
    • United Kingdom
    • Italy
    • Germany
    • Spain
  • Asia Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Middle East & Africa
    • South Africa
    • Saudi Arabia
    • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global AI in Healthcare Market.

Available Customizations:

Global AI in Healthcare Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global AI in Healthcare Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Offering (Software v/s Hardware)
    • 5.2.2. By Technology (Machine Learning, Computer Vision, Natural Language Processing, Context-Aware Computing)
    • 5.2.3. By Application (Medical Imaging & Diagnostics, Robotic Surgeries, Drug Discovery, Inpatient Care & Hospital Management, Patient Data & Risk Analysis, Others)
    • 5.2.4. By End User (Healthcare Providers, Pharmaceutical & Biotechnology Companies, Patients, Others)
    • 5.2.5. By Region
    • 5.2.6. By Company (2025)
  • 5.3. Market Map

6. North America AI in Healthcare Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Offering
    • 6.2.2. By Technology
    • 6.2.3. By Application
    • 6.2.4. By End User
    • 6.2.5. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States AI in Healthcare Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Offering
        • 6.3.1.2.2. By Technology
        • 6.3.1.2.3. By Application
        • 6.3.1.2.4. By End User
    • 6.3.2. Canada AI in Healthcare Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Offering
        • 6.3.2.2.2. By Technology
        • 6.3.2.2.3. By Application
        • 6.3.2.2.4. By End User
    • 6.3.3. Mexico AI in Healthcare Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Offering
        • 6.3.3.2.2. By Technology
        • 6.3.3.2.3. By Application
        • 6.3.3.2.4. By End User

7. Europe AI in Healthcare Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Offering
    • 7.2.2. By Technology
    • 7.2.3. By Application
    • 7.2.4. By End User
    • 7.2.5. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany AI in Healthcare Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Offering
        • 7.3.1.2.2. By Technology
        • 7.3.1.2.3. By Application
        • 7.3.1.2.4. By End User
    • 7.3.2. France AI in Healthcare Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Offering
        • 7.3.2.2.2. By Technology
        • 7.3.2.2.3. By Application
        • 7.3.2.2.4. By End User
    • 7.3.3. United Kingdom AI in Healthcare Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Offering
        • 7.3.3.2.2. By Technology
        • 7.3.3.2.3. By Application
        • 7.3.3.2.4. By End User
    • 7.3.4. Italy AI in Healthcare Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Offering
        • 7.3.4.2.2. By Technology
        • 7.3.4.2.3. By Application
        • 7.3.4.2.4. By End User
    • 7.3.5. Spain AI in Healthcare Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Offering
        • 7.3.5.2.2. By Technology
        • 7.3.5.2.3. By Application
        • 7.3.5.2.4. By End User

8. Asia Pacific AI in Healthcare Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Offering
    • 8.2.2. By Technology
    • 8.2.3. By Application
    • 8.2.4. By End User
    • 8.2.5. By Country
  • 8.3. Asia Pacific: Country Analysis
    • 8.3.1. China AI in Healthcare Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Offering
        • 8.3.1.2.2. By Technology
        • 8.3.1.2.3. By Application
        • 8.3.1.2.4. By End User
    • 8.3.2. India AI in Healthcare Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Offering
        • 8.3.2.2.2. By Technology
        • 8.3.2.2.3. By Application
        • 8.3.2.2.4. By End User
    • 8.3.3. Japan AI in Healthcare Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Offering
        • 8.3.3.2.2. By Technology
        • 8.3.3.2.3. By Application
        • 8.3.3.2.4. By End User
    • 8.3.4. South Korea AI in Healthcare Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Offering
        • 8.3.4.2.2. By Technology
        • 8.3.4.2.3. By Application
        • 8.3.4.2.4. By End User
    • 8.3.5. Australia AI in Healthcare Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Offering
        • 8.3.5.2.2. By Technology
        • 8.3.5.2.3. By Application
        • 8.3.5.2.4. By End User

9. Middle East & Africa AI in Healthcare Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Offering
    • 9.2.2. By Technology
    • 9.2.3. By Application
    • 9.2.4. By End User
    • 9.2.5. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia AI in Healthcare Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Offering
        • 9.3.1.2.2. By Technology
        • 9.3.1.2.3. By Application
        • 9.3.1.2.4. By End User
    • 9.3.2. UAE AI in Healthcare Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Offering
        • 9.3.2.2.2. By Technology
        • 9.3.2.2.3. By Application
        • 9.3.2.2.4. By End User
    • 9.3.3. South Africa AI in Healthcare Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Offering
        • 9.3.3.2.2. By Technology
        • 9.3.3.2.3. By Application
        • 9.3.3.2.4. By End User

10. South America AI in Healthcare Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Offering
    • 10.2.2. By Technology
    • 10.2.3. By Application
    • 10.2.4. By End User
    • 10.2.5. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil AI in Healthcare Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Offering
        • 10.3.1.2.2. By Technology
        • 10.3.1.2.3. By Application
        • 10.3.1.2.4. By End User
    • 10.3.2. Colombia AI in Healthcare Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Offering
        • 10.3.2.2.2. By Technology
        • 10.3.2.2.3. By Application
        • 10.3.2.2.4. By End User
    • 10.3.3. Argentina AI in Healthcare Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Offering
        • 10.3.3.2.2. By Technology
        • 10.3.3.2.3. By Application
        • 10.3.3.2.4. By End User

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Global AI in Healthcare Market: SWOT Analysis

14. Porter's Five Forces Analysis

  • 14.1. Competition in the Industry
  • 14.2. Potential of New Entrants
  • 14.3. Power of Suppliers
  • 14.4. Power of Customers
  • 14.5. Threat of Substitute Products

15. Competitive Landscape

  • 15.1. Google Health / DeepMind
    • 15.1.1. Business Overview
    • 15.1.2. Products & Services
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. SWOT Analysis
  • 15.2. Tempus AI
  • 15.3. GE Healthcare
  • 15.4. Siemens Healthineers
  • 15.5. Philips Healthcare
  • 15.6. Teladoc Health
  • 15.7. Aidoc
  • 15.8. PathAI
  • 15.9. Butterfly Network
  • 15.10. Arterys

16. Strategic Recommendations

17. About Us & Disclaimer