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到 2030 年医疗诊断中的人工智慧 (AI) 市场预测：按组件、领域、模式、AI 技术、用途、最终用户和地区进行的全球分析
市场调查报告书
商品编码
1358975

到 2030 年医疗诊断中的人工智慧 (AI) 市场预测：按组件、领域、模式、AI 技术、用途、最终用户和地区进行的全球分析

Artificial Intelligence in Medical Diagnostics Market Forecasts to 2030 - Global Analysis By Component, Specialty, Modality, AI 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 预测，2023 年全球医疗诊断领域人工智慧 (AI) 市场规模将达到 13 亿美元，预计到 2030 年将达到 105 亿美元，预测期内年复合成长率为 34.2%。 。

医疗诊断中的人工智慧 (AI) 可以帮助医疗保健专业人员为患者做出准确、及时的治疗决策，从而有可能改善护理的可及性并降低护理成本。Masu。准确诊断疾病需要多年的医学教育和大量的时间。人工智慧在医疗诊断中的应用已经证明能够提供准确的诊断、支持临床判断、提高医疗保健专业人员的判断力。

扩大医疗保健资料的可用性

电子健康记录(EHR)、医学影像资料和基因组资料等大量资料的现成可用，使得开发和检验人工智慧模型成为可能。此外，医疗保健资料的数位化和可互操作系统的引入使得收集和使用这些资料变得更加容易，使人工智慧演算法能够从不同的患者群体中学习并提高诊断准确性。我是。

预算限制

医疗保健公司面临的主要障碍是资金筹措，特别是在开发中国家，很难将 IT 资金优先于医疗设备。影像设备的高成本以及人工智慧软体的实施和许可成本是限制市场成长的主要问题，特别是在医疗报销条件较差的国家。然而，开发中国家的大多数医疗机构无力实施人工智慧解决方案，例如由于安装和维护成本高昂。这一要素阻碍了创新和尖端系统的引入。

巨量资料可用性

由于行业数位化和资讯系统的引入，巨量资料（庞大而复杂的资料）在医疗保健提供过程的各个阶段产生。医疗诊断领域的巨量资料包括点击流、网路和社交媒体互动产生的资讯、感测器、心电图、X射线等医疗设备的读数以及其他申请记录、生物识别资料等。包括。此外，近年来，巨量资料和分析解决方案变得更加复杂和广泛使用，医疗保健相关人员越来越接受电子病历、数位化检查幻灯片和高解析度放射影像。

缺乏可解释性和透明度

深度学习模型，尤其是人工智慧演算法中使用的模型，可能很复杂且难以理解。医护人员可能会发现很难信任和理解人工智慧产生的诊断背后的逻辑，因为目前尚不清楚人工智慧如何得出结论。然而，为了让人工智慧模型被医疗保健专业人员接受和认可，它们必须易于存取和检测。

COVID-19 的影响：

COVID-19 的疫情对全球医疗保健产业产生了负面影响。 COVID-19 感染率急剧上升，对全球卫生系统带来巨大压力。 COVID-19 患者通常会出现肺部问题。因此，乳房摄影筛检已成为确定COVID-19患者严重程度的标准诊断程序。 2020 年，使用 AI 诊断 COVID-19 的研究迅速增加。

软体部分预计将在预测期内成为最大的部分

诊断领域对基于人工智慧的软体及时提供准确诊断的需求不断增加，新的人工智慧演算法快速开发并核准新软体，放射科、循环系统、神经科、妇科、眼科等软体领域占据最大份额预测期内由于基于人工智慧的软体在各领域的应用。儘管面临人员短缺和影像扫描量增加的挑战，软体解决方案也为医疗保健提供者提供了相对于竞争对手的竞争优势。

预计医院领域在预测期内复合年复合成长率最高。

由于实施基于人工智慧的解决方案可实现自动化诊断和减少医院负担的要素、接受诊断程序的患者数量不断增加、对疾病早期发现的需求不断增长以及专业专家的短缺等因素，医院部门预计在整个预测期内见证盈利成长。此外，医院对用于诊断的基于人工智慧的医疗技术的需求日益增长，以减少复杂性和错误，节省金钱和时间，并由专业人员和技术纯熟劳工快速轻鬆地执行。许多医院正在与数位公司合作，为患者提供云端基础的人工智慧服务和解决方案。透过在日常业务中利用这些解决方案，医院可以提高生产力和效率。

占比最大的地区：

由于各种慢性病和感染疾病的罹患率不断上升、主要在中国和印度的人工智慧新兴企业数量不断增加，以及人工智慧填补人工智慧领域空白的巨大潜力，亚太地区将在预测期内持续成长。该地区的医疗基础设施预计将占据最大的市场份额。此外，股权投资和新兴企业的孵化也影响着区域市场的发展。该地区人口高龄化的加剧以及急性和慢性疾病患病的增加预计将支持该地区的市场扩张。

复合年复合成长率最高的地区：

由于对准确、快速诊断的需求不断增加以及世界高龄化导致慢性病发病率上升等要素，亚太地区有望盈利成长。其他好处包括帮助放射科医生解读医学影像以做出快速准确的诊断、减少医学影像中的杂讯以及以较低剂量的辐射生成高品质影像。例如，

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订阅此报告的客户可以存取以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和年复合成长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第1章执行摘要

第2章前言

  • 概述
  • 利害关係人
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 调查来源
    • 主要调查来源
    • 二次调查来源
    • 先决条件

第3章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • 新型冠状病毒感染疾病（COVID-19）的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第5章全球医疗诊断市场人工智慧（AI）：按组成部分

  • 服务
  • 软体
  • 其他组件

第6章全球医疗诊断人工智慧（AI）市场：依领域

  • 妇产科 (OB-GYN)
  • 胸部和肺部
  • 肿瘤学
  • 大脑和神经
  • 放射科
  • 其他领域

第7章全球医疗诊断人工智慧（AI）市场：按模式分类

  • 超音波
  • CT扫描
  • X射线
  • 其他方式

第8章全球医疗诊断人工智慧（AI）市场：按AI技术划分

  • 上下文感知计算
  • 机器学习
  • 电脑视觉
  • 其他人工智慧技术

第9章全球医疗诊断人工智慧（AI）市场：按用途

  • 体外诊断
  • 体内诊断
  • 临床决策支持
  • 电脑辅助诊断
  • 其他用途

第10章医疗诊断市场中的全球人工智慧 (AI)：按最终用户分类

  • 影像诊断中心
  • 医院
  • 诊断实验室
  • 其他最终用户

第11章全球人工智慧（AI）医疗诊断市场：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
    • 南美洲其他地区
  • 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

第12章进展

  • 合约、伙伴关係、协作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第13章公司简介

  • Agfa Healthcare
  • Digital Diagnostics Inc.
  • GE Healthcare
  • Google Inc
  • HeartFlow, Inc.
  • IBM Corporation
  • Imagen Technologies
  • Intel Corporation
  • International Business Machines Corporation
  • Koninklijke Philips NV
  • Microsoft Corporation
  • NovaSignal Corporation
  • Riverain Technologies
  • Siemens Healthineers AG
  • Zebra Medical Vision Inc
Product Code: SMRC23847

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Medical Diagnostics Market is accounted for $1.3 billion in 2023 and is expected to reach $10.5 billion by 2030 growing at a CAGR of 34.2% during the forecast period. By supporting healthcare professionals in making accurate and timely treatment decisions for their patients, artificial intelligence (AI) in medical diagnostics has the potential to improve access to and the cost of healthcare. It takes years of medical education and a lot of time to diagnose a condition accurately. The application of AI to medical diagnosis has demonstrated its ability to provide precise diagnoses, support clinical decisions, and improve healthcare professionals judgment.

According to the data by the World Bank, USD 1,111.082 was spent per capita on healthcare in 2018.

Market Dynamics:

Driver:

Expansion of healthcare data availability

Electronic health records (EHRs), medical imaging data, and genomic data, which have become readily available in huge amounts, have made it possible to develop and validate AI models. Moreover, the collection and use of these data have been made easier by the digitization of healthcare data and the deployment of interoperable systems, enabling AI algorithms to learn from a variety of patient groups and increase diagnostic precision.

Restraint:

Budgetary limitations

The main obstacle facing healthcare companies is funding, particularly in developing nations where it is difficult to prioritize IT funds over medical equipment. Particularly in nations where the reimbursement situation is unfavorable, the high cost of imaging equipment and the implementation and licensing expenses of AI software are the main issues limiting market growth. However, due to high installation and maintenance costs, for instance, the majority of healthcare facilities in developing nations cannot afford AI solutions. The adoption of innovative or cutting-edge systems is being hampered by this factor.

Opportunity:

Availability of big data

Big data (huge and complex data) is produced at various phases of the care delivery process as a result of the industry's growing digitization and adoption of information systems. Big data in the field of medical diagnostics includes, among other things, information generated from clickstream and web and social media interactions, readings from medical devices like sensors, ECGs, X-rays, and other billing records, as well as biometric data. Additionally, with the increasing acceptance of EHRs, digitized laboratory slides, and high-resolution radiological images among medical professionals over the past few years, big data and analytical solutions have become exponentially more advanced and widely used.

Threat:

Lack of interpretability and transparency

Deep learning models in particular, which are used in AI algorithms, can be complex and challenging to understand. Healthcare practitioners might discover it difficult to trust and comprehend the logic behind AI-generated diagnoses due to the ambiguity of how AI comes to its conclusions. However, AI models must be accessible and measurable in order to be accepted and recognized by healthcare professionals.

COVID-19 Impact:

The COVID-19 pandemic epidemic had a negative impact on the worldwide healthcare industry. The COVID-19 infection rate increased dramatically, placing an enormous burden on the global health system. Patients with COVID-19 typically experience lung problems. Therefore, to determine the severity of the disease in COVID-19 instances, cardiothoracic imaging is a standard diagnostic procedure. In 2020, the number of studies utilizing AI to diagnose COVID-19 rapidly increased.

The software segment is expected to be the largest during the forecast period

Due to the rising demand for AI-based software in diagnostics to provide an accurate diagnosis in a timely manner, the rapid development of new AI algorithms and new software approvals, and the applications of AI-based software in a variety of fields, including radiology, cardiology, neurology, gynecology, and ophthalmology, among others, the software segment held the largest share over the projection period. Additionally, despite the challenges of having a shortage of employees and the need to deal with rising imaging scan volumes, software solutions give healthcare providers a competitive edge over their rivals.

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

Due to factors like the benefits of implementing AI-based solutions to automate diagnosis and reduce workload in hospitals, the rise in the number of patients undergoing diagnostic procedures, the expanding demand for early disease detection, and the shortage of medical specialists, the hospital segment is predicted to experience profitable growth throughout the forecast period. Furthermore, there is a growing need for AI-based medical technologies in hospitals that are used for diagnosis in order to reduce complexity and errors, save money and time, and be performed quickly and easily by professionals and skilled workers. Many hospitals have partnerships with digital firms to offer cloud-based AI services and solutions to their patients. By using these solutions in their daily operations, the hospitals will increase their productivity and efficiency.

Region with largest share:

Owing to the rising incidence of various chronic and infectious diseases, the rising number of AI-based startups, particularly in China and India, and the enormous potential of AI in filling the gap in the region's healthcare infrastructure, Asia Pacific is predicted to hold the largest share over the extrapolated period. Moreover, the availability of equity investments and start-up incubation has an impact on the development of regional markets. The region's rising aging population and higher prevalence of acute and chronic illnesses are both expected to boost market expansion in the region.

Region with highest CAGR:

Due to factors including the increasing demand for accurate and prompt diagnosis and the rising frequency of chronic diseases owing to the aging population worldwide, Asia-Pacific is expected to have profitable growth. Additionally, the benefits offered by AI-based solutions in the diagnosis of different neurological diseases, such as helping radiologists interpret medical images to make a rapid and precise diagnosis, reducing noise in medical images, and producing high-quality images from lower doses of radiation, are enhancing regional growth.

Key players in the market:

Some of the key players in Artificial Intelligence (AI) in Medical Diagnostics market include: Orthofix Medical Inc., NuVasive, Inc., Baxter International Inc, OrthoPediatrics Corp., Arthrex, Inc, AlloSource, Wright Medical Group N.V., Stryker Corporation, GreenBone Ortho, Zimmer Biomet Holdings, Inc, Smith & Nephew Plc, GRAFTYS, Medtronic Plc, Bioventus Inc, Musculoskeletal Transplant Foundation, SeaSpine, GreenBone Ortho.

Key Developments:

In September 2023, IBM commits to train 2 million in artificial intelligence in three years, with a Focus on Underrepresented Communities. To achieve this goal at a global scale, IBM is expanding AI education collaborations with universities globally, collaborating with partners to deliver AI training to adult learners, and launching new generative AI coursework through IBM SkillsBuild. This will expand upon IBM's existing programs and career-building platforms to offer enhanced access to AI education and in-demand technical roles.

In September 2023, IBM is offering a robust FSMA 204 traceability and compliance management solution capable of supporting the needs of the industry's largest enterprises and suppliers of all sizes. The solution combines the scalability and interoperability of the IBM Sterling Supply Chain Intelligence Suite and the IBM Food Trust Network with iFoodDS' traceability applications and innovative food industry, regulatory, and technical expertise.

Components Covered:

  • Services
  • Software
  • Other Components

Specialties Covered:

  • Obstetrics & Gynecology (OB-GYN)
  • Chest & Lung
  • Oncology
  • Brain & Neurological
  • Radiology
  • Other Specialties

Modalities Covered:

  • Ultrasound
  • CT Scan
  • X-ray
  • Other Modalities

AI Technologies Covered:

  • Context-Aware Computing
  • Machine Learning
  • Computer Vision
  • Other AI Technologies

Applications Covered:

  • In Vitro Diagnostics
  • In Vivo Diagnostics
  • Clinical Decision Support
  • Computer-Aided Diagnosis
  • Other Applications

End Users Covered:

  • Diagnostic Imaging Centers
  • Hospitals
  • Diagnostic Laboratories
  • Other End Users

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 2021, 2022, 2023, 2026, and 2030
  • 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 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 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 Artificial Intelligence (AI) in Medical Diagnostics Market, By Component

  • 5.1 Introduction
  • 5.2 Services
  • 5.3 Software
  • 5.4 Other Components

6 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Specialty

  • 6.1 Introduction
  • 6.2 Obstetrics & Gynecology (OB-GYN)
  • 6.3 Chest & Lung
  • 6.4 Oncology
  • 6.5 Brain & Neurological
  • 6.6 Radiology
  • 6.7 Other Specialties

7 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Modality

  • 7.1 Introduction
  • 7.2 Ultrasound
  • 7.3 CT Scan
  • 7.4 X-ray
  • 7.5 Other Modalities

8 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By AI Technology

  • 8.1 Introduction
  • 8.2 Context-Aware Computing
  • 8.3 Machine Learning
  • 8.4 Computer Vision
  • 8.5 Other AI Technologies

9 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Application

  • 9.1 Introduction
  • 9.2 In Vitro Diagnostics
  • 9.3 In Vivo Diagnostics
  • 9.4 Clinical Decision Support
  • 9.5 Computer-Aided Diagnosis
  • 9.6 Other Applications

10 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By End User

  • 10.1 Introduction
  • 10.2 Diagnostic Imaging Centers
  • 10.3 Hospitals
  • 10.4 Diagnostic Laboratories
  • 10.5 Other End Users

11 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Agfa Healthcare
  • 13.2 Digital Diagnostics Inc.
  • 13.3 GE Healthcare
  • 13.4 Google Inc
  • 13.5 HeartFlow, Inc.
  • 13.6 IBM Corporation
  • 13.7 Imagen Technologies
  • 13.8 Intel Corporation
  • 13.9 International Business Machines Corporation
  • 13.10 Koninklijke Philips N.V
  • 13.11 Microsoft Corporation
  • 13.12 NovaSignal Corporation
  • 13.13 Riverain Technologies
  • 13.14 Siemens Healthineers AG
  • 13.15 Zebra Medical Vision Inc

List of Tables

  • Table 1 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Component (2021-2030) ($MN)
  • Table 3 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Services (2021-2030) ($MN)
  • Table 4 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Software (2021-2030) ($MN)
  • Table 5 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Components (2021-2030) ($MN)
  • Table 6 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Specialty (2021-2030) ($MN)
  • Table 7 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Obstetrics & Gynecology (OB-GYN) (2021-2030) ($MN)
  • Table 8 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Chest & Lung (2021-2030) ($MN)
  • Table 9 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Oncology (2021-2030) ($MN)
  • Table 10 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Brain & Neurological (2021-2030) ($MN)
  • Table 11 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Radiology (2021-2030) ($MN)
  • Table 12 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Specialties (2021-2030) ($MN)
  • Table 13 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Modality (2021-2030) ($MN)
  • Table 14 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Ultrasound (2021-2030) ($MN)
  • Table 15 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By CT Scan (2021-2030) ($MN)
  • Table 16 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By X-ray (2021-2030) ($MN)
  • Table 17 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Modalities (2021-2030) ($MN)
  • Table 18 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By AI Technology (2021-2030) ($MN)
  • Table 19 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Context-Aware Computing (2021-2030) ($MN)
  • Table 20 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Machine Learning (2021-2030) ($MN)
  • Table 21 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Computer Vision (2021-2030) ($MN)
  • Table 22 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other AI Technologies (2021-2030) ($MN)
  • Table 23 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Application (2021-2030) ($MN)
  • Table 24 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By In Vitro Diagnostics (2021-2030) ($MN)
  • Table 25 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By In Vivo Diagnostics (2021-2030) ($MN)
  • Table 26 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Clinical Decision Support (2021-2030) ($MN)
  • Table 27 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Computer-Aided Diagnosis (2021-2030) ($MN)
  • Table 28 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Applications (2021-2030) ($MN)
  • Table 29 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By End User (2021-2030) ($MN)
  • Table 30 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Diagnostic Imaging Centers (2021-2030) ($MN)
  • Table 31 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Hospitals (2021-2030) ($MN)
  • Table 32 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Diagnostic Laboratories (2021-2030) ($MN)
  • Table 33 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other End Users (2021-2030) ($MN)

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