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市场调查报告书
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1833493

机器学习/人工智慧诊断市场预测至 2032 年：按组件、诊断类型、技术、应用、最终用户和地区进行的全球分析

Machine learning / AI diagnostics Market Forecasts to 2032 - Global Analysis By Component (Software, Hardware and Services), Diagnostic Type, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球机器学习/人工智慧诊断市场预计在 2025 年达到 17 亿美元，到 2032 年将达到 81 亿美元，预测期内的复合年增长率为 24.6%。

机器学习/人工智慧诊断是指应用人工智慧演算法分析医疗数据，辅助疾病检测、诊断和决策。这些系统从大量资料集（包括医学影像、病历和检测结果）中学习，识别指示健康状况的模式和异常。透过自动化复杂的分析，人工智慧诊断可以提高临床工作流程的准确性、速度和一致性。它们支援放射科、病理科、循环系统和其他专业，提供预测性洞察并减少诊断错误。虽然人工智慧诊断并非旨在取代医疗专业人员，但它可以增强人类的专业知识，并成为改善医疗环境中患者预后的有力工具。

对早期和准确诊断的需求日益增加

对早期疾病检测和精准医疗的日益重视，推动了人工智慧诊断的应用。机器学习演算法能够分析海量医疗资料集，识别细微的模式和异常，从而实现更快、更准确的诊断。这种能力对于癌症和心血管疾病等时间敏感性疾病尤其重要。随着医疗保健系统优先考虑预防性护理并减少诊断错误，人工智慧工具对于增强临床决策和改善患者预后至关重要。

有限的临床检验

儘管AI诊断前景光明，但有限的临床检验仍是其发展的主要限制因素。许多演算法缺乏针对不同患者群体的广泛真实世界临床试验，这引发了人们对其可靠性和普遍性的担忧。监管障碍以及严格的同行评审研究需求阻碍了其应用。如果没有确切的临床证据，医疗服务提供者可能不愿意将AI工具纳入常规实务。

深度学习演算法的进展

深度学习的快速发展为人工智慧诊断开启了全新的可能性。增强型神经网路如今能够以前所未有的精确度处理复杂的医学影像、基因组数据和电子健康记录。这些创新实现了预测建模、个人化治疗建议和即时诊断支援。随着演算法变得越来越复杂且易于解读，它们也越来越容易融入临床工作流程。这些进步预计将促进跨学科创新，使人工智慧诊断更易于获取、更具可扩展性，并在全球医疗保健领域发挥更大的影响力。

实施成本高

高昂的实施成本对人工智慧诊断的广泛应用构成了重大威胁。基础设施升级、资料整合、演算法训练以及合规监管标准等相关费用可能令人望而却步，尤其对于规模较小的医疗机构。此外，持续的维护和员工培训也加重了财务负担。如果没有合适的资金筹措和报销模式，许多医疗机构可能难以证明投资的合理性，从而限制市场成长。

COVID-19的影响：

COVID-19疫情凸显了对快速、可扩展的远距离诊断解决方案的需求，并加速了人们对人工智慧诊断的兴趣。人工智慧工具被用于分析胸部扫描结果、预测病情进展并有效率地对患者进行分诊。然而，这场危机也暴露了数据品质和演算法适应性的限制。疫情虽然促进了技术创新和应用，但也凸显了严格检验和伦理部署的重要性。疫情过后，人工智慧诊断将持续发展，塑造一个具有韧性、技术主导的医疗保健体系。

诊断实验室部分预计将成为预测期内最大的部分

诊断实验室细分市场预计将在预测期内占据最大市场份额，这得益于其在临床检测和数据生成中的核心作用。这些实验室处理大量的医学影像、病理切片和检测结果，这些是机器学习演算法的理想输入。整合人工智慧工具有助于实验室提高吞吐量，减少人为错误，并提供更快、更准确的结果。这些实验室拥有完善的基础设施和丰富的数据环境，使其成为人工智慧应用的首选，从而推动了其市场份额的大幅成长。

预测期间内预计复合年增长率最高的预测部分

随着人工智慧工具越来越多地被用于预测疾病进展、治疗反应和患者预后，预计预后预测领域将在预测期内呈现最高成长率。这些预测性洞察有助于临床医生客製化干预措施并优化护理计划。随着个人化医疗和基于价值的照护需求日益增长，预后预测模型具有巨大的临床和经济价值。它们推动了医疗保健从被动转向主动的转变，从而刺激了该领域的快速成长和创新。

占比最大的地区：

在预测期内，由于医疗基础设施的不断扩张、疾病负担的不断加重以及政府的支持措施，亚太地区预计将占据最大的市场份额。中国、印度和日本等国家正大力投资数位医疗和人工智慧技术。该地区庞大的患者群体和日益普及的远端医疗为人工智慧的整合创造了肥沃的土壤。战略伙伴关係和区域创新将进一步推动市场成长，使亚太地区成为人工智慧诊断领域的全球领导者。

复合年增长率最高的地区：

预计北美地区在预测期内将实现最高的复合年增长率，这得益于其先进的医疗体系、强大的研发能力和良好的法规结构。该地区受益于人工智慧技术的早期应用、对新兴企业的强劲投资以及电子健康记录的广泛应用。科技公司与医疗机构之间的合作正在推动创新。此外，人们越来越意识到人工智慧在减少诊断错误和改善治疗效果方面的潜力，这推动了其在美国和加拿大的快速扩张。

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此报告的订阅者可以使用以下免费自订选项之一：

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    • 对最多三家其他市场公司进行全面分析
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  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
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目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 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
  • 竞争对手之间的竞争

5. 全球机器学习/人工智慧诊断市场（按组件）

  • 软体
    • 诊断影像软体
    • 电子健康记录 (EHR) 整合工具
    • 实验室资讯管理系统（LIMS）
  • 硬体
    • 影像设备
    • 诊断设备
  • 服务
    • 咨询服务
    • 维护和支援服务
    • 整合和实施服务

6. 全球机器学习/人工智慧诊断市场（按诊断类型）

  • 放射学
    • X光影像
    • 电脑断层扫描
  • 病理
    • 组织病理学
    • 细胞病理学
  • 心臟病学
    • 心电图分析
    • 心臟超音波图
  • 神经病学
    • 脑部影像
    • 脑电图分析
  • 肿瘤学
    • 肿瘤检测
    • 切片检查分析
  • 胸部和肺部
    • 肺部影像检查
    • 呼吸功能分析

7. 全球机器学习/人工智慧诊断市场（按技术）

  • 机器学习
  • 深度学习
  • 自然语言处理（NLP）
  • 电脑视觉
  • 情境感知计算

第八章全球机器学习/人工智慧诊断市场（按应用）

  • 疾病检测
  • 预后
  • 治疗计划
  • 监测和后续行动

9. 全球机器学习/人工智慧诊断市场（按最终用户）

  • 医院
  • 研究机构
  • 诊断实验室
  • 居家照护环境

第 10 章全球机器学习/人工智慧诊断市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十二章 公司概况

  • Siemens Healthineers
  • Paige AI
  • GE HealthCare
  • Qure.ai
  • Koninklijke Philips
  • Lunit
  • Aidoc
  • IBM
  • Nanox Imaging
  • InformAI
  • Riverain Technologies
  • Enlitic
  • VUNO Inc.
  • AliveCor
  • Digital Diagnostics
Product Code: SMRC31326

According to Stratistics MRC, the Global Machine learning / AI diagnostics Market is accounted for $1.7 billion in 2025 and is expected to reach $8.1 billion by 2032 growing at a CAGR of 24.6% during the forecast period. Machine learning/AI diagnostics refers to the application of artificial intelligence algorithms to analyze medical data and assist in disease detection, diagnosis, and decision-making. These systems learn from vast datasets-such as medical images, patient records, and lab results-to identify patterns and anomalies that may indicate health conditions. By automating complex analyses, AI diagnostics enhance accuracy, speed, and consistency in clinical workflows. They support radiology, pathology, cardiology, and other specialties, offering predictive insights and reducing diagnostic errors. While not a replacement for medical professionals, AI diagnostics serve as powerful tools to augment human expertise and improve patient outcomes across healthcare settings.

Market Dynamics:

Driver:

Rising Demand for Early and Accurate Diagnosis

The growing emphasis on early disease detection and precision medicine is driving the adoption of AI diagnostics. Machine learning algorithms can analyze vast medical datasets to identify subtle patterns and anomalies, enabling faster and more accurate diagnoses. This capability is especially valuable in time-sensitive conditions like cancer and cardiovascular diseases. As healthcare systems prioritize preventive care and reduce diagnostic errors, AI-powered tools are becoming indispensable in enhancing clinical decision-making and improving patient outcomes.

Restraint:

Limited Clinical Validation

Despite promising capabilities, limited clinical validation remains a major restraint for AI diagnostics. Many algorithms lack extensive real-world testing across diverse patient populations, raising concerns about reliability and generalizability. Regulatory hurdles and the need for rigorous peer-reviewed studies slow down adoption. Without robust clinical evidence, healthcare providers may hesitate to integrate AI tools into routine practice, especially in high-stakes environments.

Opportunity:

Advancements in Deep Learning Algorithms

Rapid advancements in deep learning are unlocking new opportunities in AI diagnostics. Enhanced neural networks can now process complex medical images, genomic data, and electronic health records with unprecedented accuracy. These innovations enable predictive modeling, personalized treatment recommendations, and real-time diagnostic support. As algorithms become more sophisticated and interpretable, their integration into clinical workflows becomes smoother. This evolution is expected to drive innovation across specialties, making AI diagnostics more accessible, scalable, and impactful in global healthcare.

Threat:

High Implementation Costs

High implementation costs pose a significant threat to the widespread adoption of AI diagnostics. Expenses related to infrastructure upgrades, data integration, algorithm training, and compliance with regulatory standards can be prohibitive, especially for smaller healthcare providers. Additionally, ongoing maintenance and staff training add to the financial burden. Without adequate funding or reimbursement models, many institutions may struggle to justify the investment, thus it limits market growth.

Covid-19 Impact:

The COVID-19 pandemic accelerated interest in AI diagnostics by highlighting the need for rapid, scalable, and remote diagnostic solutions. AI tools were deployed to analyze chest scans, predict disease progression, and triage patients efficiently. However, the crisis also exposed limitations in data quality and algorithm adaptability. While the pandemic catalyzed innovation and adoption, it underscored the importance of robust validation and ethical deployment. Post-pandemic, AI diagnostics continue to evolve, shaping resilient and tech-driven healthcare systems.

The diagnostic laboratories segment is expected to be the largest during the forecast period

The diagnostic laboratories segment is expected to account for the largest market share during the forecast period due to its central role in clinical testing and data generation. These labs handle vast volumes of medical images, pathology slides, and lab results-ideal inputs for machine learning algorithms. By integrating AI tools, laboratories can enhance throughput, reduce human error, and deliver faster, more accurate results. Their established infrastructure and data-rich environment make them prime candidates for AI adoption, driving significant market share.

The prognosis prediction segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the prognosis prediction segment is predicted to witness the highest growth rate because AI-powered tools are increasingly used to forecast disease progression, treatment response, and patient outcomes. These predictive insights help clinicians tailor interventions and optimize care plans. With growing demand for personalized medicine and value-based care, prognosis prediction models offer immense clinical and economic value. Their ability to transform reactive care into proactive management is fueling rapid growth and innovation in this segment.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to its expanding healthcare infrastructure, rising disease burden, and supportive government initiatives. Countries like China, India, and Japan are investing heavily in digital health and AI technologies. The region's large patient population and increasing adoption of telemedicine create fertile ground for AI integration. Strategic partnerships and local innovation further accelerate market growth, positioning Asia Pacific as a global leader in AI diagnostics.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR owing to advanced healthcare systems, strong R&D capabilities, and favorable regulatory frameworks. The region benefits from early adoption of AI technologies, robust investment in startups, and widespread use of electronic health records. Collaborations between tech companies and medical institutions foster innovation. Additionally, growing awareness of AI's potential to reduce diagnostic errors and improve outcomes is propelling rapid expansion across the U.S. and Canada.

Key players in the market

Some of the key players in Machine learning / AI diagnostics Market include Siemens Healthineers, Paige AI, GE HealthCare, Qure.ai, Koninklijke Philips, Lunit, Aidoc, IBM, Nanox Imaging, InformAI, Riverain Technologies, Enlitic, VUNO Inc., AliveCor and Digital Diagnostics.

Key Developments:

In September 2025, Lantheus Holdings and GE HealthCare have entered into an exclusive licensing agreement granting GE HealthCare rights to develop, manufacture, and commercialize Lantheus' prostate cancer imaging agent, PYLARIFY(R) (piflufolastat F18), in Japan. This partnership aims to enhance prostate cancer diagnostics in Japan, addressing a significant clinical need in the world's third-largest prostate cancer market.

In April 2025, IBM and Tokyo Electron (TEL) have renewed their collaboration with a new five-year agreement, focusing on advancing semiconductor and chiplet technologies to support the demands of generative AI. This partnership leverages IBM's expertise in semiconductor process integration and TEL's leading-edge equipment to explore smaller nodes and chiplet architectures, aiming to achieve the performance and energy efficiency requirements for the future of generative AI.

Components Covered:

  • Software
  • Hardware
  • Services

Diagnostic Types Covered:

  • Radiology
  • Pathology
  • Cardiology
  • Neurology
  • Oncology
  • Chest & Lung

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Context-Aware Computing

Applications Covered:

  • Disease Detection
  • Prognosis Prediction
  • Treatment Planning
  • Monitoring & Follow-up

End Users Covered:

  • Hospitals
  • Research Institutions
  • Diagnostic Laboratories
  • Home Care Settings

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & 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 2024, 2025, 2026, 2028, and 2032
  • 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

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Machine learning / AI diagnostics Market, By Component

  • 5.1 Introduction
  • 5.2 Software
    • 5.2.1 Diagnostic Imaging Software
    • 5.2.2 Electronic Health Records (EHR) Integration Tools
    • 5.2.3 Laboratory Information Management Systems (LIMS)
  • 5.3 Hardware
    • 5.3.1 Imaging Devices
    • 5.3.2 Diagnostic Instruments
  • 5.4 Services
    • 5.4.1 Consulting Services
    • 5.4.2 Maintenance & Support Services
    • 5.4.3 Integration & Implementation Services

6 Global Machine learning / AI diagnostics Market, By Diagnostic Type

  • 6.1 Introduction
  • 6.2 Radiology
    • 6.2.1 X-ray Imaging
    • 6.2.2 CT Scans
  • 6.3 Pathology
    • 6.3.1 Histopathology
    • 6.3.2 Cytopathology
  • 6.4 Cardiology
    • 6.4.1 ECG Analysis
    • 6.4.2 Echocardiography
  • 6.5 Neurology
    • 6.5.1 Brain Imaging
    • 6.5.2 EEG Analysis
  • 6.6 Oncology
    • 6.6.1 Tumor Detection
    • 6.6.2 Biopsy Analysis
  • 6.7 Chest & Lung
    • 6.7.1 Pulmonary Imaging
    • 6.7.2 Respiratory Function Analysis

7 Global Machine learning / AI diagnostics Market, By Technology

  • 7.1 Introduction
  • 7.2 Machine Learning
  • 7.3 Deep Learning
  • 7.4 Natural Language Processing (NLP)
  • 7.5 Computer Vision
  • 7.6 Context-Aware Computing

8 Global Machine learning / AI diagnostics Market, By Application

  • 8.1 Introduction
  • 8.2 Disease Detection
  • 8.3 Prognosis Prediction
  • 8.4 Treatment Planning
  • 8.5 Monitoring & Follow-up

9 Global Machine learning / AI diagnostics Market, By End User

  • 9.1 Introduction
  • 9.2 Hospitals
  • 9.3 Research Institutions
  • 9.4 Diagnostic Laboratories
  • 9.5 Home Care Settings

10 Global Machine learning / AI diagnostics Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Siemens Healthineers
  • 12.2 Paige AI
  • 12.3 GE HealthCare
  • 12.4 Qure.ai
  • 12.5 Koninklijke Philips
  • 12.6 Lunit
  • 12.7 Aidoc
  • 12.8 IBM
  • 12.9 Nanox Imaging
  • 12.10 InformAI
  • 12.11 Riverain Technologies
  • 12.12 Enlitic
  • 12.13 VUNO Inc.
  • 12.14 AliveCor
  • 12.15 Digital Diagnostics

List of Tables

  • Table 1 Global Machine learning / AI diagnostics Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Machine learning / AI diagnostics Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Machine learning / AI diagnostics Market Outlook, By Software (2024-2032) ($MN)
  • Table 4 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Imaging Software (2024-2032) ($MN)
  • Table 5 Global Machine learning / AI diagnostics Market Outlook, By Electronic Health Records (EHR) Integration Tools (2024-2032) ($MN)
  • Table 6 Global Machine learning / AI diagnostics Market Outlook, By Laboratory Information Management Systems (LIMS) (2024-2032) ($MN)
  • Table 7 Global Machine learning / AI diagnostics Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 8 Global Machine learning / AI diagnostics Market Outlook, By Imaging Devices (2024-2032) ($MN)
  • Table 9 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Instruments (2024-2032) ($MN)
  • Table 10 Global Machine learning / AI diagnostics Market Outlook, By Services (2024-2032) ($MN)
  • Table 11 Global Machine learning / AI diagnostics Market Outlook, By Consulting Services (2024-2032) ($MN)
  • Table 12 Global Machine learning / AI diagnostics Market Outlook, By Maintenance & Support Services (2024-2032) ($MN)
  • Table 13 Global Machine learning / AI diagnostics Market Outlook, By Integration & Implementation Services (2024-2032) ($MN)
  • Table 14 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Type (2024-2032) ($MN)
  • Table 15 Global Machine learning / AI diagnostics Market Outlook, By Radiology (2024-2032) ($MN)
  • Table 16 Global Machine learning / AI diagnostics Market Outlook, By X-ray Imaging (2024-2032) ($MN)
  • Table 17 Global Machine learning / AI diagnostics Market Outlook, By CT Scans (2024-2032) ($MN)
  • Table 18 Global Machine learning / AI diagnostics Market Outlook, By Pathology (2024-2032) ($MN)
  • Table 19 Global Machine learning / AI diagnostics Market Outlook, By Histopathology (2024-2032) ($MN)
  • Table 20 Global Machine learning / AI diagnostics Market Outlook, By Cytopathology (2024-2032) ($MN)
  • Table 21 Global Machine learning / AI diagnostics Market Outlook, By Cardiology (2024-2032) ($MN)
  • Table 22 Global Machine learning / AI diagnostics Market Outlook, By ECG Analysis (2024-2032) ($MN)
  • Table 23 Global Machine learning / AI diagnostics Market Outlook, By Echocardiography (2024-2032) ($MN)
  • Table 24 Global Machine learning / AI diagnostics Market Outlook, By Neurology (2024-2032) ($MN)
  • Table 25 Global Machine learning / AI diagnostics Market Outlook, By Brain Imaging (2024-2032) ($MN)
  • Table 26 Global Machine learning / AI diagnostics Market Outlook, By EEG Analysis (2024-2032) ($MN)
  • Table 27 Global Machine learning / AI diagnostics Market Outlook, By Oncology (2024-2032) ($MN)
  • Table 28 Global Machine learning / AI diagnostics Market Outlook, By Tumor Detection (2024-2032) ($MN)
  • Table 29 Global Machine learning / AI diagnostics Market Outlook, By Biopsy Analysis (2024-2032) ($MN)
  • Table 30 Global Machine learning / AI diagnostics Market Outlook, By Chest & Lung (2024-2032) ($MN)
  • Table 31 Global Machine learning / AI diagnostics Market Outlook, By Pulmonary Imaging (2024-2032) ($MN)
  • Table 32 Global Machine learning / AI diagnostics Market Outlook, By Respiratory Function Analysis (2024-2032) ($MN)
  • Table 33 Global Machine learning / AI diagnostics Market Outlook, By Technology (2024-2032) ($MN)
  • Table 34 Global Machine learning / AI diagnostics Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 35 Global Machine learning / AI diagnostics Market Outlook, By Deep Learning (2024-2032) ($MN)
  • Table 36 Global Machine learning / AI diagnostics Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 37 Global Machine learning / AI diagnostics Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 38 Global Machine learning / AI diagnostics Market Outlook, By Context-Aware Computing (2024-2032) ($MN)
  • Table 39 Global Machine learning / AI diagnostics Market Outlook, By Application (2024-2032) ($MN)
  • Table 40 Global Machine learning / AI diagnostics Market Outlook, By Disease Detection (2024-2032) ($MN)
  • Table 41 Global Machine learning / AI diagnostics Market Outlook, By Prognosis Prediction (2024-2032) ($MN)
  • Table 42 Global Machine learning / AI diagnostics Market Outlook, By Treatment Planning (2024-2032) ($MN)
  • Table 43 Global Machine learning / AI diagnostics Market Outlook, By Monitoring & Follow-up (2024-2032) ($MN)
  • Table 44 Global Machine learning / AI diagnostics Market Outlook, By End User (2024-2032) ($MN)
  • Table 45 Global Machine learning / AI diagnostics Market Outlook, By Hospitals (2024-2032) ($MN)
  • Table 46 Global Machine learning / AI diagnostics Market Outlook, By Research Institutions (2024-2032) ($MN)
  • Table 47 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Laboratories (2024-2032) ($MN)
  • Table 48 Global Machine learning / AI diagnostics Market Outlook, By Home Care Settings (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.