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市場調查報告書
商品編碼
2074909

人工智慧驅動的診斷市場預測至2034年：按診斷方式、部署模式、技術、應用、最終用戶和地區分類的全球分析

AI-Powered Diagnostics Market Forecasts to 2034 - Global Analysis By Diagnostic Modality, Deployment Model, 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，全球人工智慧診斷市場規模將達到 103 億美元，在預測期內以 46.1% 的複合年成長率成長，到 2034 年將達到 2,132 億美元。

人工智慧驅動的診斷系統利用機器學習和神經網路等先進演算法，輔助醫療專業人員進行疾病檢測和分析。這些工具處理大量的臨床訊息，包括影像資料、電子健康記錄和檢測結果，從而產生準確及時的診斷資訊。人工智慧透過最大限度地減少診斷錯誤和提高模式識別能力，提升了臨床決策的品質。人工智慧已廣泛應用於放射學、病理學和循環系統等專業領域。此外，這項技術有助於疾病的早期發現，支持個人化治療策略，並透過持續的臨床改進，為全球醫療保健系統帶來更好的醫療效果。

根據英國放射學院統計，2021年英國放射科專科醫師缺口達1,939人，佔放射科醫師總數的33%。預計到2025年，這一缺口將達到3,600人。人才短缺是推動人工智慧診斷技術普及以滿足日益成長的需求的主要動力。

慢性病盛行率增加

癌症、心臟病、糖尿病和神經系統疾病等慢性疾病負擔日益加重，大大推動了對人工智慧診斷解決方案的需求。這些疾病通常需要早期發現和持續監測，而人工智慧系統能夠有效地實現這些目標。人工智慧工具透過處理醫學影像、病患記錄和臨床數據，幫助及早發現異常模式。隨著全球慢性病病例的增加，醫療機構越來越依賴人工智慧技術來提高診斷的準確性和速度。這項日益嚴峻的健康挑戰正在推動全球醫療機構採用先進的以人工智慧為基礎的診斷系統。

實施和整合成本高昂

實施人工智慧診斷解決方案的高昂成本是其市場擴張的主要障礙。醫院和醫療機構需要投入大量資金用於先進的運算系統、軟體工具、雲端服務和專業技術人員，才能採用這些技術。小規模的醫療機構往往因為資金有限而舉步維艱。此外，將人工智慧平台與現有臨床系統和工作流程整合也需要額外的投資和技術投入。持續的維護、更新和系統改進也會增加長期成本。因此，高昂的初始投資和營運成本阻礙了人工智慧診斷工具在全球醫療機構的快速普及。

遠端醫療和遠距保健的擴展

遠端醫療和遠距保健服務的日益普及為人工智慧診斷技術帶來了巨大的發展機會。人工智慧工具與遠端醫療系統結合，可以遠端評估患者的症狀、醫學影像和健康記錄。這使得醫生無需面對面會診即可提供快速可靠的診斷，這對於醫療資源匱乏的農村地區和醫療服務不足的地區尤其重要。隨著數位醫療解決方案在全球範圍內的日益普及，人工智慧診斷可以改善遠距監測，擴大醫療服務的覆蓋範圍，並提高全球各醫療領域的線上諮詢效率。

倫理問題和算法偏見

倫理問題和演算法偏差對基於人工智慧的診斷系統的發展構成重大風險。人工智慧模型若使用有限或不具代表性的資料集進行訓練，可能會產生偏差或錯誤的結果，進而影響不同病患小組的診斷準確性。這引發了人們對醫療服務公平性、安全性和公正性的擔憂。此外，缺乏對人工智慧決策過程的清晰解釋會降低臨床醫生對這些工具的信任度。這些問題也可能導致監管和法律上的挑戰。如果沒有充分的安全措施、資料校正和監督，這些倫理限制可能會阻礙人工智慧診斷在全球的普及應用。

新型冠狀病毒（COVID-19）的影響：

新冠疫情加速了數位醫療技術的應用，對人工智慧診斷產業產生了重大影響。醫院和醫療系統面臨巨大壓力，對快速、精準的診斷方法的需求激增。人工智慧在分析診斷影像、追蹤感染途徑以及早期檢測新冠病毒方面發揮了關鍵作用。疫情危機也促進了人工智慧醫療解決方案的資金投入，並加速了遠端醫療的普及。另一方面，供應鏈和研發活動的中斷導致研發進程暫時放緩。總體而言，疫情顯著推動了人工智慧診斷技術在全球的長期發展。

在預測期內，醫療影像領域預計將佔據最大的市場佔有率。

鑑於診斷影像技術在識別和評估各種疾病方面的廣泛應用，預計在預測期內，該領域將佔據最大的市場佔有率。在放射學領域，人工智慧正被積極應用於高效分析X光、 電腦斷層掃描、MRI掃描和超音波檢查影像。醫療機構進行的大量診斷影像檢查顯著推動了該領域人工智慧工具的應用。人工智慧透過先進的模式識別技術改進影像解讀，從而實現疾病的早期發現和更恰當的臨床決策。與醫院系統的無縫整合使診斷影像成為全球最主要的細分市場。

在預測期內，「在家辦公/遠距辦公用戶」細分市場預計將呈現最高的複合年成長率。

在預測期內，「家庭和遠距用戶」細分市場預計將呈現最高的成長率，這主要得益於對個人化居家醫療服務需求的不斷成長。遠端醫療平台、穿戴式健康追蹤器和行動醫療應用程式的日益普及，使患者能夠在舒適的家中獲得診斷支援。人工智慧技術能夠實現持續監測、症狀評估和健康問題的早期發現，而無需前往醫療機構。除了對便利且價格合理的醫療保健服務日益成長的需求外，慢性病盛行率的上升和人口老化也推動了該細分市場的強勁成長，使其成為人工智慧診斷市場中成長最快的類別。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其高度發達的醫療保健體系、先進數位技術的快速普及以及強大的AI和醫療技術公司生態系統。該地區受益於對醫療保健創新的巨額投資、廣泛的研究活動以及電子健康記錄系統的廣泛應用。美國透過在醫療機構中率先採用AI診斷解決方案，在推動市場需求方面發揮關鍵作用。此外，支持性的法律規範和報銷機制也促進了這些解決方案的普及。高額的醫療費用支出和強大的技術實力使北美在區域市場中佔據領先地位。

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，這主要得益於醫療保健系統的持續改進和數位醫療技術的快速普及。龐大的人口基數、慢性病盛行率的上升以及醫療保健服務可近性的提高，都在推動對先進診斷工具的需求。中國、印度和日本等國家正大力投資，將人工智慧融入醫療保健服務。人們對早期診斷和預防醫學的日益重視也促進了市場擴張。此外，價格合理的AI解決方案正在推動全部區域醫療機構和診斷中心的廣泛應用。

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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
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧診斷市場：以診斷方式分類

  • 診斷影像
  • 臨床試驗
  • 即時診斷
  • 數位和虛擬診斷

第6章：全球人工智慧診斷市場：按部署模式分類

  • 基於雲端的AI診斷
  • 本地部署人工智慧診斷
  • 混合實現

第7章：全球人工智慧診斷市場：按技術分類

  • 機器學習和深度學習模型
  • 自然語言處理（NLP）
  • 電腦視覺
  • 預測分析與決策支援系統

第8章：全球人工智慧診斷市場：按應用分類

  • 腫瘤診斷
  • 心血管診斷
  • 神經學診斷
  • 感染疾病診斷
  • 代謝和內分泌診斷
  • 罕見疾病和基因診斷

第9章：全球人工智慧診斷市場：按最終用戶分類

  • 醫院和診所
  • 診斷檢查室
  • 研究和學術機構
  • 家庭用戶和遠端用戶

第10章：全球人工智慧診斷市場：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11章 策略市場資訊

  • 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12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13章：公司簡介

  • Aidoc
  • Viz.ai
  • Zebra Medical Vision
  • Qure.ai
  • Arterys
  • Butterfly Network
  • Caption Health
  • DeepMind Health
  • Paige AI
  • PathAI
  • Tempus
  • Therapixel
  • Nuance Communications
  • Siemens Healthineers
  • GE Healthcare
  • Philips Healthcare
  • Canon Medical Systems
  • Hologic
Product Code: SMRC37409

According to Stratistics MRC, the Global AI-Powered Diagnostics Market is accounted for $10.3 billion in 2026 and is expected to reach $213.2 billion by 2034 growing at a CAGR of 46.1% during the forecast period. Artificial intelligence-driven diagnostic systems leverage advanced algorithms, including machine learning and neural networks, to support healthcare professionals in disease detection and analysis. These tools process vast amounts of clinical information such as imaging scans, electronic health records, and laboratory results to generate precise and timely diagnostic insights. By minimizing diagnostic errors and enhancing pattern recognition capabilities, AI improves the quality of clinical decisions. It is extensively applied in specialties like radiology, pathology, and cardiology. Furthermore, this technology facilitates early identification of diseases, supports customized treatment strategies, and enhances overall healthcare outcomes across global medical systems today with continuous clinical improvement.

According to the Royal College of Radiologists (UK), there was a shortage of 1,939 consultant radiologists in 2021-equivalent to 33% of the workforce-with projections of a 3,600 shortfall by 2025. This workforce gap is a key driver for adopting AI-powered diagnostics to meet rising demand.

Market Dynamics:

Driver:

Rising prevalence of chronic diseases

The growing burden of long-term illnesses like cancer, heart disease, diabetes, and neurological disorders is strongly driving the demand for AI-powered diagnostic solutions. These health conditions often need early identification and continuous evaluation, which artificial intelligence systems can effectively provide. By processing medical images, patient records, and clinical data, AI tools help detect abnormal patterns at an early stage. With the global rise in chronic disease cases, healthcare providers are increasingly relying on AI technologies to enhance diagnostic precision and speed. This escalating health challenge is fueling the adoption of advanced AI-based diagnostic systems across healthcare facilities globally.

Restraint:

High implementation and integration costs

The expensive nature of deploying AI-driven diagnostic solutions is a key barrier to market expansion. Hospitals and healthcare facilities need to spend heavily on advanced computing systems, software tools, cloud services, and trained professionals to implement these technologies. Smaller healthcare providers often struggle due to limited financial capacity. Moreover, combining AI platforms with existing clinical systems and workflows demands additional investment and technical effort. Continuous maintenance, updates, and system improvements also increase long-term costs. Consequently, the significant upfront expenditure and operational expenses restrict the faster adoption of AI-powered diagnostic tools across healthcare organizations worldwide.

Opportunity:

Expansion of telemedicine and remote healthcare

The increasing adoption of telemedicine and remote healthcare services creates strong growth opportunities for AI-based diagnostic technologies. Artificial intelligence tools can be combined with telehealth systems to evaluate patient symptoms, medical images, and health records from a distance. This enables doctors to provide quick and reliable diagnoses without in-person consultations. It is particularly valuable in rural and underserved areas where healthcare access is limited. With the global rise of digital healthcare solutions, AI diagnostics can improve remote monitoring, expand healthcare reach, and enhance the effectiveness of virtual medical consultations across various healthcare sectors worldwide.

Threat:

Ethical concerns and algorithmic bias

Ethical issues and bias in algorithms represent a major risk to the growth of AI-based diagnostic systems. Artificial intelligence models may generate skewed or incorrect results when trained on limited or unrepresentative datasets, potentially affecting diagnosis accuracy across different patient groups. This creates concerns about fairness, safety, and equality in healthcare services. Moreover, the lack of clear explanation in AI decision-making reduces clinician confidence in these tools. Such problems may also lead to regulatory and legal challenges. Without proper safeguards, data correction, and oversight, these ethical limitations could restrict the widespread adoption of AI diagnostics worldwide.

Covid-19 Impact:

The COVID-19 outbreak greatly influenced the AI-powered diagnostics industry by speeding up the use of digital healthcare technologies. Hospitals and health systems were under extreme pressure, increasing demand for quick and precise diagnostic methods. Artificial intelligence played a key role in analyzing imaging scans, tracking disease transmission, and identifying COVID-19 infections early. The crisis also boosted funding in AI healthcare solutions and strengthened telemedicine adoption. At the same time, interruptions in supply chains and research activities caused temporary delays in development. Overall, the pandemic significantly advanced the long-term expansion of AI-based diagnostic technologies worldwide.

The imaging diagnostics segment is expected to be the largest during the forecast period

The imaging diagnostics segment is expected to account for the largest market share during the forecast period because of its broad application in identifying and assessing various medical conditions. Artificial intelligence is heavily utilized in radiology departments to analyze medical images such as X-rays, CT scans, MRI scans, and ultrasound reports efficiently. The large number of imaging procedures performed in healthcare facilities significantly supports the adoption of AI-based tools in this area. AI enhances image interpretation through advanced pattern recognition, allowing earlier detection of diseases and better clinical decisions. Its seamless integration into hospital systems makes imaging diagnostics the most dominant segment globally.

The home & remote users segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the home & remote users segment is predicted to witness the highest growth rate because of the rising preference for personalized and home-based healthcare services. The increasing use of telehealth platforms, wearable health trackers, and mobile medical applications allows patients to receive diagnostic support from their homes. AI technologies enable continuous monitoring, symptom evaluation, and early detection of health issues without visiting healthcare facilities. The growing need for convenient and affordable healthcare, along with increasing chronic diseases and aging populations, is driving strong expansion in this segment, making it the fastest-growing category in the AI diagnostics market.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share because of its highly developed healthcare system, rapid adoption of advanced digital technologies, and strong ecosystem of AI and medical technology companies. The region is supported by heavy investments in healthcare innovation, extensive research activities, and widespread integration of electronic health record systems. The United States plays a key role in driving demand through early implementation of AI diagnostic solutions across healthcare facilities. In addition, supportive regulatory frameworks and reimbursement structures encourage adoption. High healthcare expenditure and strong technological capability position North America as the top regional market.

Region with highest CAGR:

Over the forecast period, the Asia-Pacific region is anticipated to exhibit the highest CAGR because of ongoing enhancements in healthcare systems and rapid uptake of digital medical technologies. A large population base, rising cases of chronic illnesses and improving healthcare accessibility are fueling demand for advanced diagnostic tools. Countries like China, India, and Japan are making significant investments in incorporating artificial intelligence into healthcare services. Growing awareness about early diagnosis and preventive care is also contributing to market expansion. Moreover, affordable AI-based solutions are encouraging widespread adoption across healthcare facilities and diagnostic centers throughout the region.

Key players in the market

Some of the key players in AI-Powered Diagnostics Market include Aidoc, Viz.ai, Zebra Medical Vision, Qure.ai, Arterys, Butterfly Network, Caption Health, DeepMind Health, Paige AI, PathAI, Tempus, Therapixel, Nuance Communications, Siemens Healthineers, GE Healthcare, Philips Healthcare, Canon Medical Systems and Hologic.

Key Developments:

In April 2026, GE HealthCare announced an expanded collaboration with DeepHealth, Inc, to further the innovation, commercialization, and adoption of advanced AI-powered mammography tools. The announcement coincides with the Society of Breast Imaging (SBI) Annual Symposium, where GE HealthCare will showcase its latest advancements in breast imaging and women's health.

In February 2026, Siemens Healthineers and Mayo Clinic are expanding their strategic collaboration to enhance patient care for neurodegenerative disease and the management of prostate cancer and metastatic liver tumors. The two organizations have signed an agreement that will improve care for those disease states and expand access to new imaging and interventional technologies.

Diagnostic Modalities Covered:

  • Imaging Diagnostics
  • Laboratory Diagnostics
  • Point-of-Care Diagnostics
  • Digital & Virtual Diagnostics

Deployment Models Covered:

  • Cloud-Based AI Diagnostics
  • On-Premise AI Diagnostics
  • Hybrid Deployment

Technologies Covered:

  • Machine Learning & Deep Learning Models
  • Natural Language Processing (NLP)
  • Computer Vision
  • Predictive Analytics & Decision Support Systems

Applications Covered:

  • Oncology Diagnostics
  • Cardiovascular Diagnostics
  • Neurological Diagnostics
  • Infectious Disease Diagnostics
  • Metabolic & Endocrine Diagnostics
  • Rare Disease & Genetic Diagnostics

End Users Covered:

  • Hospitals & Clinics
  • Diagnostic Laboratories
  • Research & Academic Institutes
  • Home & Remote Users

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-Powered Diagnostics Market, By Diagnostic Modality

  • 5.1 Imaging Diagnostics
  • 5.2 Laboratory Diagnostics
  • 5.3 Point-of-Care Diagnostics
  • 5.4 Digital & Virtual Diagnostics

6 Global AI-Powered Diagnostics Market, By Deployment Model

  • 6.1 Cloud-Based AI Diagnostics
  • 6.2 On-Premise AI Diagnostics
  • 6.3 Hybrid Deployment

7 Global AI-Powered Diagnostics Market, By Technology

  • 7.1 Machine Learning & Deep Learning Models
  • 7.2 Natural Language Processing (NLP)
  • 7.3 Computer Vision
  • 7.4 Predictive Analytics & Decision Support Systems

8 Global AI-Powered Diagnostics Market, By Application

  • 8.1 Oncology Diagnostics
  • 8.2 Cardiovascular Diagnostics
  • 8.3 Neurological Diagnostics
  • 8.4 Infectious Disease Diagnostics
  • 8.5 Metabolic & Endocrine Diagnostics
  • 8.6 Rare Disease & Genetic Diagnostics

9 Global AI-Powered Diagnostics Market, By End User

  • 9.1 Hospitals & Clinics
  • 9.2 Diagnostic Laboratories
  • 9.3 Research & Academic Institutes
  • 9.4 Home & Remote Users

10 Global AI-Powered Diagnostics Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 Aidoc
  • 13.2 Viz.ai
  • 13.3 Zebra Medical Vision
  • 13.4 Qure.ai
  • 13.5 Arterys
  • 13.6 Butterfly Network
  • 13.7 Caption Health
  • 13.8 DeepMind Health
  • 13.9 Paige AI
  • 13.10 PathAI
  • 13.11 Tempus
  • 13.12 Therapixel
  • 13.13 Nuance Communications
  • 13.14 Siemens Healthineers
  • 13.15 GE Healthcare
  • 13.16 Philips Healthcare
  • 13.17 Canon Medical Systems
  • 13.18 Hologic

List of Tables

  • Table 1 Global AI-Powered Diagnostics Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Powered Diagnostics Market Outlook, By Diagnostic Modality (2023-2034) ($MN)
  • Table 3 Global AI-Powered Diagnostics Market Outlook, By Imaging Diagnostics (2023-2034) ($MN)
  • Table 4 Global AI-Powered Diagnostics Market Outlook, By Laboratory Diagnostics (2023-2034) ($MN)
  • Table 5 Global AI-Powered Diagnostics Market Outlook, By Point-of-Care Diagnostics (2023-2034) ($MN)
  • Table 6 Global AI-Powered Diagnostics Market Outlook, By Digital & Virtual Diagnostics (2023-2034) ($MN)
  • Table 7 Global AI-Powered Diagnostics Market Outlook, By Deployment Model (2023-2034) ($MN)
  • Table 8 Global AI-Powered Diagnostics Market Outlook, By Cloud-Based AI Diagnostics (2023-2034) ($MN)
  • Table 9 Global AI-Powered Diagnostics Market Outlook, By On-Premise AI Diagnostics (2023-2034) ($MN)
  • Table 10 Global AI-Powered Diagnostics Market Outlook, By Hybrid Deployment (2023-2034) ($MN)
  • Table 11 Global AI-Powered Diagnostics Market Outlook, By Technology (2023-2034) ($MN)
  • Table 12 Global AI-Powered Diagnostics Market Outlook, By Machine Learning & Deep Learning Models (2023-2034) ($MN)
  • Table 13 Global AI-Powered Diagnostics Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 14 Global AI-Powered Diagnostics Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 15 Global AI-Powered Diagnostics Market Outlook, By Predictive Analytics & Decision Support Systems (2023-2034) ($MN)
  • Table 16 Global AI-Powered Diagnostics Market Outlook, By Application (2023-2034) ($MN)
  • Table 17 Global AI-Powered Diagnostics Market Outlook, By Oncology Diagnostics (2023-2034) ($MN)
  • Table 18 Global AI-Powered Diagnostics Market Outlook, By Cardiovascular Diagnostics (2023-2034) ($MN)
  • Table 19 Global AI-Powered Diagnostics Market Outlook, By Neurological Diagnostics (2023-2034) ($MN)
  • Table 20 Global AI-Powered Diagnostics Market Outlook, By Infectious Disease Diagnostics (2023-2034) ($MN)
  • Table 21 Global AI-Powered Diagnostics Market Outlook, By Metabolic & Endocrine Diagnostics (2023-2034) ($MN)
  • Table 22 Global AI-Powered Diagnostics Market Outlook, By Rare Disease & Genetic Diagnostics (2023-2034) ($MN)
  • Table 23 Global AI-Powered Diagnostics Market Outlook, By End User (2023-2034) ($MN)
  • Table 24 Global AI-Powered Diagnostics Market Outlook, By Hospitals & Clinics (2023-2034) ($MN)
  • Table 25 Global AI-Powered Diagnostics Market Outlook, By Diagnostic Laboratories (2023-2034) ($MN)
  • Table 26 Global AI-Powered Diagnostics Market Outlook, By Research & Academic Institutes (2023-2034) ($MN)
  • Table 27 Global AI-Powered Diagnostics Market Outlook, By Home & Remote Users (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.