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市场调查报告书
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1871278

人工智慧在诊断领域的市场机会、成长驱动因素、产业趋势分析及预测（2025-2034年）

Artificial Intelligence In Diagnostics Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034
出版日期: | 出版商: Global Market Insights Inc. | 英文 160 Pages | 商品交期: 2-3个工作天内

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简介目录

2024 年全球人工智慧诊断市场价值为 15 亿美元，预计到 2034 年将以 21.5% 的复合年增长率增长至 105 亿美元。

人工智慧在诊断市场的应用 - IMG1

市场成长的驱动力来自对疾病早期检测、人工智慧在医学影像中的应用、精准诊断以及合规性提升等方面的日益增长的需求。人工智慧解决方案正帮助医疗服务提供者、支付方、生命科学机构和医疗技术公司改善患者预后、优化营运并满足合规标准。关键解决方案包括基于人工智慧的影像和诊断软体、数位病理平台以及预测分析工具，这些工具能够自动识别疾病、辅助制定精准的治疗方案并提升医疗品质。云端人工智慧应用、数位病理和预测建模技术的进步正在拓展人工智慧在放射学、心臟病学、肿瘤学和病理学等领域的应用。监管机构的批准和相关框架鼓励将人工智慧融入临床工作流程，进一步推动了市场普及。医疗机构、技术供应商和生命科学公司之间不断增加的研究投入和策略合作正在推动创新，并加速人工智慧在全球的应用。

市场范围
起始年份 2024
预测年份 2025-2034
起始值 15亿美元
预测值 105亿美元
复合年增长率 21.5%

2024年，诊断实验室领域的市场规模达到3.561亿美元，预计到2034年将以22.3%的复合年增长率成长。由于实验室在各种临床应用中发挥着至关重要的作用，例如筛检、分析和报告医疗结果，因此它们是人工智慧技术的主要使用者。日益复杂的工作流程、不断增长的样本量以及对高通量检测的需求，都在推动对人工智慧驱动的自动化和决策支援系统的需求。

2024年，放射学领域占据了28.4%的市场份额，预计到2034年将达到30亿美元。由于迫切需要快速、精准的影像分析以早期发现疾病，放射学在诊断市场中引领人工智慧的发展。慢性病和急性病患病率的不断上升，也推高了对医学影像检查的需求。基于人工智慧的放射学解决方案能够自动解读影像，最大限度地减少人为错误，并更快提供结果，从而支援及时制定治疗方案。

2024年，北美人工智慧诊断市场占40.7%的份额。该地区的领先地位归功于其先进的医疗基础设施、数位技术的广泛应用以及大量的研发投入。人工智慧驱动的医学影像、预测分析和数位病理平台已在医院、诊所和实验室广泛普及。此外，包括心血管疾病、癌症和神经系统疾病在内的慢性病盛行率不断上升，也推动了该地区对早期精准诊断的需求。

全球全球诊断市场的主要参与者包括Aidoc、AliveCor、Digital Diagnostics、Enlitic、HeartFlow、Imagen、NVIDIA、PathAI、Qure.ai、Riverain Technologies、西门子医疗、Sophia Genetics、Tempus、Ultromics、Viz.ai、Vuno和Zebra Vision。为了巩固自身地位，人工智慧诊断市场的企业正在实施多种策略。这些策略包括：扩大研发能力以创新人工智慧演算法并提高预测准确性；与医疗服务提供者、实验室和科技公司建立策略合作伙伴关係；以及收购小型公司以增强技术组合。许多企业正致力于遵守监管规定并获得批准，以加速市场准入。此外，企业还优先考虑基于云端和软体即服务（SaaS）的解决方案，以拓展市场并提供可扩展、用户友好的平台。

目录

第一章：方法论与范围

第二章：执行概要

第三章：行业洞察

  • 产业生态系分析
  • 产业影响因素
    • 成长驱动因素
      • 慢性病盛行率上升
      • 对人工智慧工具的需求不断增长
      • 技术进步
      • 政府的利多措施和资金
    • 产业陷阱与挑战
      • 高昂的采购和维护成本
      • 资料隐私和安全问题
    • 市场机会
      • 新兴经济体的扩张
      • 与远距医疗和远距诊断的整合
  • 成长潜力分析
  • 监管环境
    • 北美洲
    • 欧洲
    • 亚太地区
    • 拉丁美洲
  • 技术格局
    • 当前技术趋势
      • 人工智慧驱动的放射学和病理学成像软体
      • 用于快速异常检测的机器学习演算法
      • 与医院工作流程整合的数位病理平台
    • 新兴技术
      • 人工智慧驱动的多模态成像技术用于综合诊断
      • 用于早期癌症和慢性病检测的深度学习演算法
      • 面向可扩展诊断解决方案的云端人工智慧平台
  • 差距分析
  • 波特的分析
  • PESTEL 分析
  • 未来市场趋势
    • 人工智慧诊断在新兴市场的扩展
    • 与远距医疗和远距患者监测相结合
    • 利用人工智慧洞察力实现精准医疗和个人化医疗的普及

第四章：竞争格局

  • 介绍
  • 公司矩阵分析
  • 公司市占率分析
    • 全球的
    • 北美洲
    • 欧洲
    • 亚太地区
    • 拉丁美洲
  • 竞争定位矩阵
  • 主要市场参与者的竞争分析
  • 关键进展
    • 併购
    • 合作伙伴关係与合作
    • 新服务类型推出
    • 扩张计划

第五章：市场估算与预测：依组件划分，2021-2034年

  • 主要趋势
  • 软体
  • 服务
  • 硬体

第六章：市场估算与预测：依应用领域划分，2021-2034年

  • 主要趋势
  • 放射科
  • 肿瘤学
  • 心臟病学
  • 神经病学
  • 病理
  • 传染病
  • 其他应用

第七章：市场估算与预测：依最终用途划分，2021-2034年

  • 主要趋势
  • 医院和诊所
  • 诊断实验室
  • 影像中心
  • 其他最终用途

第八章：市场估算与预测：依地区划分，2021-2034年

  • 主要趋势
  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 西班牙
    • 义大利
    • 荷兰
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 澳洲
    • 韩国
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • 中东和非洲
    • 南非
    • 沙乌地阿拉伯
    • 阿联酋

第九章：公司简介

  • Aidoc
  • AliveCor
  • Digital Diagnostics
  • Enlitic
  • HeartFlow
  • Imagen
  • NVIDIA
  • PathAI
  • Qure.ai
  • Riverain Technologies
  • Siemens Healthineers
  • Sophia Genetics
  • Tempus
  • Ultromics
  • Viz.ai
  • Vuno
  • Zebra Medical Vision
简介目录
Product Code: 11036

The Global Artificial Intelligence In Diagnostics Market was valued at USD 1.5 billion in 2024 and is estimated to grow at a CAGR of 21.5% to reach USD 10.5 billion by 2034.

Artificial Intelligence In Diagnostics Market - IMG1

The market is being propelled by increasing demand for early disease detection, AI integration in medical imaging, precision diagnostics, and regulatory compliance facilitation. AI-powered solutions are enabling healthcare providers, payers, life sciences organizations, and health technology companies to improve patient outcomes, optimize operations, and meet compliance standards. Key solutions include AI-based imaging and diagnostic software, digital pathology platforms, and predictive analytics tools that automate disease identification, assist in accurate treatment planning, and enhance care quality. Advancements in cloud-based AI applications, digital pathology, and predictive modeling are broadening the use of AI across radiology, cardiology, oncology, and pathology. Market adoption is further supported by regulatory approvals and frameworks that encourage the integration of AI into clinical workflows. Increasing research investments and strategic partnerships among healthcare institutions, technology providers, and life sciences firms are driving innovation and accelerating adoption worldwide.

Market Scope
Start Year2024
Forecast Year2025-2034
Start Value$1.5 Billion
Forecast Value$10.5 Billion
CAGR21.5%

The diagnostic laboratories segment generated USD 356.1 million in 2024 and is expected to grow at a CAGR of 22.3% through 2034. Laboratories are major users of AI technologies due to their critical role in screening, analyzing, and reporting medical results across a variety of clinical applications. Rising workflow complexity, growing sample volumes, and the need for high-throughput testing are driving the demand for AI-driven automation and decision support systems.

The radiology segment held a 28.4% share in 2024 and is projected to reach USD 3 billion by 2034. Radiology leads the Artificial Intelligence in the diagnostics market because of the urgent need for rapid and precise imaging analysis to detect diseases at early stages. The increasing prevalence of chronic and acute conditions has raised the demand for medical imaging tests. AI-based radiology solutions automate image interpretation, minimize human error, and deliver faster results, enabling timely treatment decisions.

North America Artificial Intelligence In Diagnostics Market held a 40.7% share in 2024. The region's leadership is attributed to advanced healthcare infrastructure, widespread adoption of digital technologies, and significant research and development investments. AI-driven medical imaging, predictive analytics, and digital pathology platforms are widely available across hospitals, clinics, and laboratories. Additionally, the growing prevalence of chronic conditions, including cardiovascular diseases, cancer, and neurological disorders, is driving demand for early and precise diagnostics in the region.

Key players operating in the Global Artificial Intelligence In Diagnostics Market include Aidoc, AliveCor, Digital Diagnostics, Enlitic, HeartFlow, Imagen, NVIDIA, PathAI, Qure.ai, Riverain Technologies, Siemens Healthineers, Sophia Genetics, Tempus, Ultromics, Viz.ai, Vuno, and Zebra Medical Vision. To strengthen their position, companies in the Artificial Intelligence In Diagnostics Market are implementing a variety of strategies. These include expanding research and development capabilities to innovate new AI algorithms and improve predictive accuracy, forming strategic partnerships with healthcare providers, laboratories, and technology firms, and acquiring smaller companies to enhance technological portfolios. Many organizations are focusing on regulatory compliance and obtaining approvals to accelerate market entry. Companies are also prioritizing cloud-based and software-as-a-service solutions to reach broader markets while offering scalable, user-friendly platforms.

Table of Contents

Chapter 1 Methodology and Scope

  • 1.1 Market scope and definitions
  • 1.2 Research design
    • 1.2.1 Research approach
    • 1.2.2 Data collection methods
  • 1.3 Data mining sources
    • 1.3.1 Global
    • 1.3.2 Regional/country
  • 1.4 Base estimates and calculations
    • 1.4.1 Base year calculation
    • 1.4.2 Key trends for market estimation
  • 1.5 Primary research and validation
    • 1.5.1 Primary sources
  • 1.6 Forecast model
  • 1.7 Research assumptions and limitations

Chapter 2 Executive Summary

  • 2.1 Industry 3600 synopsis
  • 2.2 Key market trends
    • 2.2.1 Regional trends
    • 2.2.2 Component trends
    • 2.2.3 Application trends
    • 2.2.4 End Use trends
  • 2.3 CXO perspectives: Strategic imperatives
    • 2.3.1 Key decision points for industry executives
    • 2.3.2 Critical success factors for market players
  • 2.4 Future outlook and strategic recommendations

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
  • 3.2 Industry impact forces
    • 3.2.1 Growth drivers
      • 3.2.1.1 Rising prevalence of chronic diseases
      • 3.2.1.2 Increasing demand for AI tools
      • 3.2.1.3 Technological advancements
      • 3.2.1.4 Favourable government initiatives and funding
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High procurement and maintenance costs
      • 3.2.2.2 Data privacy and security concerns
    • 3.2.3 Market opportunities
      • 3.2.3.1 Expansion in emerging economies
      • 3.2.3.2 Integration with telemedicine and remote diagnostics
  • 3.3 Growth potential analysis
  • 3.4 Regulatory landscape
    • 3.4.1 North America
    • 3.4.2 Europe
    • 3.4.3 Asia Pacific
    • 3.4.4 LAMEA
  • 3.5 Technology landscape
    • 3.5.1 Current technological trends
      • 3.5.1.1 AI-powered radiology and pathology imaging software
      • 3.5.1.2 Machine learning algorithms for rapid anomaly detection
      • 3.5.1.3 Digital pathology platforms integrated with hospital workflows
    • 3.5.2 Emerging technologies
      • 3.5.2.1 AI-driven multi-modal imaging for integrated diagnostics
      • 3.5.2.2 Deep learning algorithms for early cancer and chronic disease detection
      • 3.5.2.3 Cloud-based AI platforms for scalable diagnostics solutions
  • 3.6 Gap analysis
  • 3.7 Porter's analysis
  • 3.8 PESTEL analysis
  • 3.9 Future market trends
    • 3.9.1 Expansion of AI diagnostics in emerging markets
    • 3.9.2 Integration with telemedicine and remote patient monitoring
    • 3.9.3 Adoption of precision and personalized medicine using AI insights

Chapter 4 Competitive Landscape, 2024

  • 4.1 Introduction
  • 4.2 Company matrix analysis
  • 4.3 Company market share analysis
    • 4.3.1 Global
    • 4.3.2 North America
    • 4.3.3 Europe
    • 4.3.4 Asia Pacific
    • 4.3.5 LAMEA
  • 4.4 Competitive positioning matrix
  • 4.5 Competitive analysis of major market players
  • 4.6 Key developments
    • 4.6.1 Mergers & acquisitions
    • 4.6.2 Partnerships & collaborations
    • 4.6.3 New service type launches
    • 4.6.4 Expansion plans

Chapter 5 Market Estimates and Forecast, By Component, 2021 - 2034 ($ Mn)

  • 5.1 Key trends
  • 5.2 Software
  • 5.3 Services
  • 5.4 Hardware

Chapter 6 Market Estimates and Forecast, By Application, 2021 - 2034 ($ Mn)

  • 6.1 Key trends
  • 6.2 Radiology
  • 6.3 Oncology
  • 6.4 Cardiology
  • 6.5 Neurology
  • 6.6 Pathology
  • 6.7 Infectious diseases
  • 6.8 Other applications

Chapter 7 Market Estimates and Forecast, By End Use, 2021 - 2034 ($ Mn)

  • 7.1 Key trends
  • 7.2 Hospitals & clinics
  • 7.3 Diagnostic laboratories
  • 7.4 Imaging centers
  • 7.5 Other End Use

Chapter 8 Market Estimates and Forecast, By Region, 2021 - 2034 ($ Mn)

  • 8.1 Key trends
  • 8.2 North America
    • 8.2.1 U.S.
    • 8.2.2 Canada
  • 8.3 Europe
    • 8.3.1 Germany
    • 8.3.2 UK
    • 8.3.3 France
    • 8.3.4 Spain
    • 8.3.5 Italy
    • 8.3.6 Netherlands
  • 8.4 Asia Pacific
    • 8.4.1 China
    • 8.4.2 Japan
    • 8.4.3 India
    • 8.4.4 Australia
    • 8.4.5 South Korea
  • 8.5 Latin America
    • 8.5.1 Brazil
    • 8.5.2 Mexico
    • 8.5.3 Argentina
  • 8.6 Middle East and Africa
    • 8.6.1 South Africa
    • 8.6.2 Saudi Arabia
    • 8.6.3 UAE

Chapter 9 Company Profiles

  • 9.1 Aidoc
  • 9.2 AliveCor
  • 9.3 Digital Diagnostics
  • 9.4 Enlitic
  • 9.5 HeartFlow
  • 9.6 Imagen
  • 9.7 NVIDIA
  • 9.8 PathAI
  • 9.9 Qure.ai
  • 9.10 Riverain Technologies
  • 9.11 Siemens Healthineers
  • 9.12 Sophia Genetics
  • 9.13 Tempus
  • 9.14 Ultromics
  • 9.15 Viz.ai
  • 9.16 Vuno
  • 9.17 Zebra Medical Vision