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市場調查報告書
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2068756

人工智慧驅動的大規模篩檢市場預測至2034年：全球分析（按組件、部署模式、技術、篩選類型、應用、最終用戶和地區分類）

AI-Based Population Screening Market Forecasts to 2034 - Global Analysis By Component (Software, Hardware and Services), Deployment Mode, Technology, Screening Type, 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，全球人工智慧驅動的大規模篩檢市場預計將在 2026 年達到 37 億美元，到 2034 年達到 164 億美元，在預測期內以 20.4% 的複合年成長率成長。

人工智慧驅動的人群篩檢是指利用機器學習、深度學習和電腦視覺技術，大規模分析醫學影像、基因組數據和臨床記錄，以早期發現癌症、心血管疾病、糖尿病和神經系統疾病等疾病的舉措。這些平台使醫療系統和公共衛生機構能夠實施大規模、具成本效益的篩檢項目，其敏感度和特異性都高於傳統的人工影像判讀方法。這有助於更早識別高風險族群並及時採取預防干預措施，從而改善治療效果並降低長期醫療成本。

非傳染性疾病負擔日益加重，早期檢測的重要性日益凸顯

癌症、心血管疾病和糖尿病等非傳染性疾病在全球整體死亡和醫療保健支出中佔據相當大的比例，其預後與確診時的疾病分期直接相關。人工智慧篩檢平台能夠利用基於數百萬病例訓練的演算法分析影像資料和生物標記物，從而顯著提高早期檢出率，識別出人眼檢查可能遺漏的細微疾病徵兆。公共衛生機構和國家癌症篩檢計畫正日益探索利用人工智慧技術擴大篩檢計畫的能力，解決區域間篩檢資源分配不均的問題，並減輕放射科專家解讀影像的負擔。

法規核准的時間表和臨床檢驗要求

在大多數司法管轄區，應用於診斷和篩檢工作流程的人工智慧篩檢演算法都受到嚴格的監管流程約束，需要進行廣泛的臨床檢驗研究，以證明其在不同患者群體中的表現與既定的標準療法相當或更優。除了這些檢驗項目的成本和耗時之外，不同市場中針對人工智慧/機器學習醫療設備的法規結構不斷演變且有時不一致，也對商業部署構成了重大障礙。上市後監測義務進一步增加了持續的合規成本，而可能改變效能特徵的演算法更新則可能觸發檢驗的要求。

人工智慧驅動的基因組和多模態篩檢計畫的擴展

基因測序、多組體學分析和人工智慧的整合為下一代人群定序平台提供了前所未有的機遇，使其能夠在臨床症狀出現數年前識別疾病風險。人工智慧增強的多基因風險評分能夠以前所未有的精準度對人群遺傳性癌症、心血管疾病和罕見疾病的風險進行分層，從而實現對高風險人群的靶向預防干預。採用整合影像、基因組和臨床數據的多模態篩檢平台的醫療系統，將擁有卓越的篩檢能力，並在蓬勃發展的精準預防市場中建立強大的競爭優勢。

不同人口群體間演算法表現的差異損害了公平性。

人工智慧驅動的人群篩檢面臨的主要擔憂之一是，基於特定人口群體資料訓練的演算法在應用於被低估的人群時可能表現不佳。研究表明，人工智慧篩檢工具在不同種族、民族和社會經濟群體中存在性能差異，這引發了人們的擔憂：未經適當人口統計檢驗就引入演算法，可能會加劇現有的健康不平等。監管機構和健康公平倡導者正日益嚴格地審查人工智慧篩檢工具的檢驗方法，要求開發者證明其在不同人群中表現穩定，並持續監測其在特定人口群體中的表現下降。

新型冠狀病毒（COVID-19）的影響：

新冠疫情雖然擾亂了人工智慧驅動的大規模篩檢市場，但最終也加速了其發展。短期來看，疫情導致的預約名額限制影響了選擇性篩檢項目，造成癌症和心血管疾病篩檢嚴重延誤，早期檢出率下降。然而，疫情也提升了人們對人工智慧輔助篩檢解決方案的興趣，這類方案能夠在有限的篩檢能力下優先識別高風險族群，使醫療系統能夠最大限度地利用有限的預約名額。疫情過後，世界各國政府都在投資人工智慧驅動的篩檢基礎設施，以解決積壓的未處理篩檢樣本，並建構能夠在未來公共衛生突發事件中維持篩檢能力的彈性計畫。

在預測期內，軟體領域預計將佔據最大的市場佔有率。

在預測期內，軟體領域預計將佔據最大的市場佔有率。這主要歸功於醫療機構、診斷中心和公共衛生組織對人工智慧篩檢平台、診斷演算法解決方案和影像分析軟體的廣泛採用。雲端託管的篩檢軟體平台使醫療機構能夠獲取不斷改進的演算法，而無需在專用人工智慧硬體上進行資本投資。

在預測期內，生成式人工智慧細分市場預計將呈現最高的複合年成長率。

在預測期內，生成式人工智慧領域預計將呈現最高的成長率，因為研究人員和開發人員將利用基礎模型創建合成醫學影像資料集，從而克服訓練高效能篩檢演算法時資料不足的限制。此外，生成式人工智慧能夠開發多模態篩檢模型，這些模型可以整合來自多種模態（例如圖像、基因組和臨床數據）的信息，與單模態演算法相比，有望提供更優異的篩檢性能。

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。這得歸功於其完善的國家癌症篩檢計畫、龐大的醫學影像處理量以及已批准多種人工智慧篩檢演算法商業應用的積極法規環境。該地區先進的基因組基礎設施和不斷成長的消費者基因檢測市場也進一步擴大了人工智慧篩檢的潛在市場機會。

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，這主要歸因於該地區存在大規模篩檢不足的人群、公共衛生部門對癌症和慢性病篩檢計畫的投入不斷增加，以及與擴充放射科專科醫生隊伍相比，採用人工智慧更具成本效益。中國和印度的國家醫療衛生現代化計畫均包含對人工智慧診斷的大量投資，而東南亞的醫療衛生系統正在部署人工智慧篩檢工具，以便為那些難以獲得訓練有素的放射科醫生服務的農村和郊區居民提供專科級別的診斷能力。

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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：全球人工智慧驅動的大規模篩檢市場：按組件分類

  • 軟體
    • 人工智慧篩檢平台
    • 診斷演算法
    • 數據分析解決方案
    • 影像分析軟體
  • 硬體
    • 醫療影像設備
    • 診斷設備
    • 邊緣人工智慧設備
  • 服務
    • 諮詢服務
    • 整合與部署
    • 培訓和支援服務
    • 託管服務

第6章：全球人工智慧驅動的大規模篩檢市場：按部署模式分類

  • 現場
  • 基於雲端的
  • 混合實現

第7章：全球人工智慧驅動的大規模篩檢市場：按技術分類

  • 機器學習
  • 深度學習
  • 自然語言處理（NLP）
  • 電腦視覺
  • 預測分析
  • 人工智慧世代
  • 巨量資料分析

第8章：全球人工智慧驅動的大規模篩檢市場：按篩檢類型分類

  • 癌症篩檢
  • 心血管疾病篩檢
  • 糖尿病篩檢
  • 神經系統疾病篩檢
  • 傳染病篩檢
  • 基因和基因組篩檢
  • 眼科篩檢

第9章：全球人工智慧驅動的大規模健康篩檢市場：按應用領域分類

  • 風險評估和分層
  • 疾病早期發現
  • 臨床決策支持
  • 預測性人口健康分析
  • 遠距患者篩檢
  • 公共衛生監測
  • 個人化預防醫學

第10章：全球人工智慧驅動的大規模健康篩檢市場：按最終用戶分類

  • 醫院和診所
  • 診斷中心
  • 政府和公共衛生機構
  • 研究機構
  • 醫療保健支付方
  • 企業健康服務提供者

第11章：全球人工智慧驅動的大規模健康篩檢市場：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12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13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14章：公司簡介

  • Siemens Healthineers AG
  • GE HealthCare Technologies Inc.
  • Koninklijke Philips NV
  • Fujifilm Holdings Corporation
  • Canon Medical Systems Corporation
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Tempus AI, Inc.
  • Aidoc Medical Ltd.
  • Qure.ai Technologies Pvt. Ltd.
  • ScreenPoint Medical BV
  • Riverain Technologies LLC
  • Zebra Medical Vision Ltd.
  • Nanox Imaging Ltd.
Product Code: SMRC37061

According to Stratistics MRC, the Global AI-Based Population Screening Market is accounted for $3.7 billion in 2026 and is expected to reach $16.4 billion by 2034, growing at a CAGR of 20.4% during the forecast period. AI-based population screening encompasses the deployment of machine learning, deep learning, and computer vision technologies to analyze medical imaging, genomic data, and clinical records at population scale for the early detection of diseases including cancer, cardiovascular disorders, diabetes, and neurological conditions. These platforms enable healthcare systems and public health agencies to conduct large-scale, cost-effective screening programs with greater sensitivity and specificity than traditional manual interpretation methods, identifying at-risk individuals earlier and enabling timely preventive interventions that improve outcomes and reduce long-term treatment costs.

Market Dynamics:

Driver:

Increasing burden of non-communicable diseases and imperative for early detection

Non-communicable diseases including cancer, cardiovascular disease, and diabetes collectively account for a substantial proportion of global mortality and healthcare expenditure, with outcomes directly correlated to stage at detection. AI-powered screening platforms can dramatically enhance early detection rates by analyzing imaging data and biomarkers with algorithms trained on millions of cases, identifying subtle disease signatures that may be missed by human review. Public health agencies and national cancer screening programs are increasingly evaluating AI augmentation to extend screening program capacity, improve geographic equity of access, and reduce the interpretation workload on specialist radiologists.

Restraint:

Regulatory approval timelines and clinical validation requirements

AI screening algorithms applied to diagnostic and screening workflows are subject to rigorous regulatory pathways in most jurisdictions, requiring extensive clinical validation studies demonstrating performance equivalence or superiority to established standards of care across diverse patient populations. The cost and duration of these validation programs, combined with the evolving and sometimes inconsistent regulatory frameworks for AI/ML-based medical devices across different markets, create significant barriers to commercial deployment. Post-market surveillance obligations further increase ongoing compliance costs, and any algorithm updates that may alter performance characteristics can trigger re-validation requirements.

Opportunity:

Expansion of AI-driven genomic and multi-modal screening programs

The convergence of genomic sequencing, multi-omics analysis, and AI creates extraordinary opportunities for next-generation population screening platforms capable of identifying disease risk years before clinical manifestation. Polygenic risk scores augmented by AI algorithms can stratify population risk for hereditary cancers, cardiovascular conditions, and rare diseases with unprecedented precision, enabling targeted preventive interventions for high-risk individuals. Healthcare systems adopting multi-modal screening platforms that integrate imaging, genomic, and clinical data are positioned to deliver superior screening performance and build defensible competitive advantages in the growing precision prevention market.

Threat:

Algorithmic performance disparities across demographic groups undermining equity

A significant concern in AI-based population screening is the potential for algorithms trained predominantly on data from certain demographic groups to demonstrate degraded performance when applied to underrepresented populations. Research has identified performance disparities in AI screening tools across racial, ethnic, and socioeconomic groups, raising concerns about exacerbating existing health inequities if algorithms are deployed without appropriate demographic validation. Regulatory agencies and health equity advocates are increasingly scrutinizing AI screening tool validation methodologies, requiring developers to demonstrate consistent performance across diverse populations and implement ongoing monitoring for demographic-specific performance degradation.

Covid-19 Impact:

The COVID-19 pandemic both disrupted and ultimately catalyzed the AI-based population screening market. In the short term, suspension of elective screening programs due to pandemic-related capacity constraints resulted in significant backlogs for cancer and cardiovascular screening, worsening early detection rates. However, the crisis simultaneously accelerated interest in AI-assisted screening solutions capable of prioritizing high-risk individuals within constrained screening capacity, enabling health systems to maximize the clinical impact of limited appointment availability. Post-pandemic, governments are investing in AI screening infrastructure to address accumulated screening backlogs and build resilient programs capable of maintaining throughput during future public health emergencies.

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

The software segment is expected to account for the largest market share during the forecast period, driven by broad adoption of AI screening platforms, diagnostic algorithm solutions, and imaging analytics software across healthcare providers, diagnostic centers, and public health agencies. Cloud-hosted screening software platforms offer healthcare organizations access to continuously improving algorithms without capital investment in specialized AI hardware.

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

Over the forecast period, the Generative AI segment is predicted to witness the highest growth rate, as researchers and developers leverage foundation models to create synthetic medical imaging datasets that address data scarcity limitations in training high-performance screening algorithms. Generative AI also enables the development of multi-modal screening models that can synthesize information across imaging, genomic, and clinical data modalities, potentially delivering superior screening performance compared to single-modality algorithms.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by well-established national cancer screening programs, high medical imaging volume, and a progressive regulatory environment that has cleared multiple AI screening algorithms for commercial use. The region's advanced genomics infrastructure and growing direct-to-consumer genetic testing market further expand the addressable AI screening opportunity.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by large underscreened populations, expanding public health investment in cancer and chronic disease screening programs, and cost-effective AI deployment economics relative to specialist radiologist workforce expansion. China and India's national healthcare modernization agendas include substantial AI diagnostic investment, while Southeast Asian health systems are adopting AI screening tools to extend specialist-equivalent diagnostic capabilities to rural and peri-urban populations with limited access to trained radiologists.

Key players in the market

Some of the key players in AI-Based Population Screening Market include Siemens Healthineers AG, GE HealthCare Technologies Inc., Koninklijke Philips N.V., Fujifilm Holdings Corporation, Canon Medical Systems Corporation, IBM Corporation, Microsoft Corporation, Google LLC, Tempus AI, Inc., Aidoc Medical Ltd., Qure.ai Technologies Pvt. Ltd., ScreenPoint Medical BV, Riverain Technologies LLC, Zebra Medical Vision Ltd., Nanox Imaging Ltd.

Key Developments:

In March 2026, Qure.ai Technologies Pvt. Ltd. secured regulatory clearance in multiple Asian markets for its AI-based chest X-ray screening platform designed for large-scale population tuberculosis detection, enabling deployment in government-sponsored national TB elimination programs.

In January 2026, Google LLC announced an expanded deployment of its AI-powered mammography screening algorithm across a network of European radiology centers, following clinical validation studies demonstrating superior cancer detection rates compared to standard double-reader protocols in prospective clinical evaluation.

Components Covered:

  • Software
  • Hardware
  • Services

Functions Covered:

  • On-Premises
  • Cloud-Based
  • Hybrid Deployment

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Predictive Analytics
  • Generative AI
  • Big Data Analytics

Delivery Models Covered:

  • Cancer Screening
  • Cardiovascular Disease Screening
  • Diabetes Screening
  • Neurological Disorder Screening
  • Infectious Disease Screening
  • Genetic and Genomic Screening
  • Ophthalmic Screening

Applications Covered:

  • Risk Assessment and Stratification
  • Early Disease Detection
  • Clinical Decision Support
  • Predictive Population Health Analytics
  • Remote Patient Screening
  • Public Health Surveillance
  • Personalized Preventive Care

End Users Covered:

  • Hospitals and Clinics
  • Diagnostic Centers
  • Government and Public Health Agencies
  • Research Institutes
  • Healthcare Payers
  • Corporate Wellness Providers

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-Based Population Screening Market, By Component

  • 5.1 Software
    • 5.1.1 AI Screening Platforms
    • 5.1.2 Diagnostic Algorithms
    • 5.1.3 Data Analytics Solutions
    • 5.1.4 Imaging Analytics Software
  • 5.2 Hardware
    • 5.2.1 Imaging Devices
    • 5.2.2 Diagnostic Equipment
    • 5.2.3 Edge AI Devices
  • 5.3 Services
    • 5.3.1 Consulting Services
    • 5.3.2 Integration & Deployment
    • 5.3.3 Training & Support Services
    • 5.3.4 Managed Services

6 Global AI-Based Population Screening Market, By Deployment Mode

  • 6.1 On-Premises
  • 6.2 Cloud-Based
  • 6.3 Hybrid Deployment

7 Global AI-Based Population Screening Market, By Technology

  • 7.1 Machine Learning
  • 7.2 Deep Learning
  • 7.3 Natural Language Processing (NLP)
  • 7.4 Computer Vision
  • 7.5 Predictive Analytics
  • 7.6 Generative AI
  • 7.7 Big Data Analytics

8 Global AI-Based Population Screening Market, By Screening Type

  • 8.1 Cancer Screening
  • 8.2 Cardiovascular Disease Screening
  • 8.3 Diabetes Screening
  • 8.4 Neurological Disorder Screening
  • 8.5 Infectious Disease Screening
  • 8.6 Genetic and Genomic Screening
  • 8.7 Ophthalmic Screening

9 Global AI-Based Population Screening Market, By Application

  • 9.1 Risk Assessment and Stratification
  • 9.2 Early Disease Detection
  • 9.3 Clinical Decision Support
  • 9.4 Predictive Population Health Analytics
  • 9.5 Remote Patient Screening
  • 9.6 Public Health Surveillance
  • 9.7 Personalized Preventive Care

10 Global AI-Based Population Screening Market, By End User

  • 10.1 Hospitals and Clinics
  • 10.2 Diagnostic Centers
  • 10.3 Government and Public Health Agencies
  • 10.4 Research Institutes
  • 10.5 Healthcare Payers
  • 10.6 Corporate Wellness Providers

11 Global AI-Based Population Screening Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 Siemens Healthineers AG
  • 14.2 GE HealthCare Technologies Inc.
  • 14.3 Koninklijke Philips N.V.
  • 14.4 Fujifilm Holdings Corporation
  • 14.5 Canon Medical Systems Corporation
  • 14.6 IBM Corporation
  • 14.7 Microsoft Corporation
  • 14.8 Google LLC
  • 14.9 Tempus AI, Inc.
  • 14.10 Aidoc Medical Ltd.
  • 14.11 Qure.ai Technologies Pvt. Ltd.
  • 14.12 ScreenPoint Medical BV
  • 14.13 Riverain Technologies LLC
  • 14.14 Zebra Medical Vision Ltd.
  • 14.15 Nanox Imaging Ltd.

List of Tables

  • Table 1 Global AI-Based Population Screening Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Based Population Screening Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI-Based Population Screening Market Outlook, By Software (2023-2034) ($MN)
  • Table 4 Global AI-Based Population Screening Market Outlook, By AI Screening Platforms (2023-2034) ($MN)
  • Table 5 Global AI-Based Population Screening Market Outlook, By Diagnostic Algorithms (2023-2034) ($MN)
  • Table 6 Global AI-Based Population Screening Market Outlook, By Data Analytics Solutions (2023-2034) ($MN)
  • Table 7 Global AI-Based Population Screening Market Outlook, By Imaging Analytics Software (2023-2034) ($MN)
  • Table 8 Global AI-Based Population Screening Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 9 Global AI-Based Population Screening Market Outlook, By Imaging Devices (2023-2034) ($MN)
  • Table 10 Global AI-Based Population Screening Market Outlook, By Diagnostic Equipment (2023-2034) ($MN)
  • Table 11 Global AI-Based Population Screening Market Outlook, By Edge AI Devices (2023-2034) ($MN)
  • Table 12 Global AI-Based Population Screening Market Outlook, By Services (2023-2034) ($MN)
  • Table 13 Global AI-Based Population Screening Market Outlook, By Consulting Services (2023-2034) ($MN)
  • Table 14 Global AI-Based Population Screening Market Outlook, By Integration & Deployment (2023-2034) ($MN)
  • Table 15 Global AI-Based Population Screening Market Outlook, By Training & Support Services (2023-2034) ($MN)
  • Table 16 Global AI-Based Population Screening Market Outlook, By Managed Services (2023-2034) ($MN)
  • Table 17 Global AI-Based Population Screening Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 18 Global AI-Based Population Screening Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 19 Global AI-Based Population Screening Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 20 Global AI-Based Population Screening Market Outlook, By Hybrid Deployment (2023-2034) ($MN)
  • Table 21 Global AI-Based Population Screening Market Outlook, By Technology (2023-2034) ($MN)
  • Table 22 Global AI-Based Population Screening Market Outlook, By Machine Learning (2023-2034) ($MN)
  • Table 23 Global AI-Based Population Screening Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 24 Global AI-Based Population Screening Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 25 Global AI-Based Population Screening Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 26 Global AI-Based Population Screening Market Outlook, By Predictive Analytics (2023-2034) ($MN)
  • Table 27 Global AI-Based Population Screening Market Outlook, By Generative AI (2023-2034) ($MN)
  • Table 28 Global AI-Based Population Screening Market Outlook, By Big Data Analytics (2023-2034) ($MN)
  • Table 29 Global AI-Based Population Screening Market Outlook, By Screening Type (2023-2034) ($MN)
  • Table 30 Global AI-Based Population Screening Market Outlook, By Cancer Screening (2023-2034) ($MN)
  • Table 31 Global AI-Based Population Screening Market Outlook, By Cardiovascular Disease Screening (2023-2034) ($MN)
  • Table 32 Global AI-Based Population Screening Market Outlook, By Diabetes Screening (2023-2034) ($MN)
  • Table 33 Global AI-Based Population Screening Market Outlook, By Neurological Disorder Screening (2023-2034) ($MN)
  • Table 34 Global AI-Based Population Screening Market Outlook, By Infectious Disease Screening (2023-2034) ($MN)
  • Table 35 Global AI-Based Population Screening Market Outlook, By Genetic and Genomic Screening (2023-2034) ($MN)
  • Table 36 Global AI-Based Population Screening Market Outlook, By Ophthalmic Screening (2023-2034) ($MN)
  • Table 37 Global AI-Based Population Screening Market Outlook, By Application (2023-2034) ($MN)
  • Table 38 Global AI-Based Population Screening Market Outlook, By Risk Assessment and Stratification (2023-2034) ($MN)
  • Table 39 Global AI-Based Population Screening Market Outlook, By Early Disease Detection (2023-2034) ($MN)
  • Table 40 Global AI-Based Population Screening Market Outlook, By Clinical Decision Support (2023-2034) ($MN)
  • Table 41 Global AI-Based Population Screening Market Outlook, By Predictive Population Health Analytics (2023-2034) ($MN)
  • Table 42 Global AI-Based Population Screening Market Outlook, By Remote Patient Screening (2023-2034) ($MN)
  • Table 43 Global AI-Based Population Screening Market Outlook, By Public Health Surveillance (2023-2034) ($MN)
  • Table 44 Global AI-Based Population Screening Market Outlook, By Personalized Preventive Care (2023-2034) ($MN)
  • Table 45 Global AI-Based Population Screening Market Outlook, By End User (2023-2034) ($MN)
  • Table 46 Global AI-Based Population Screening Market Outlook, By Hospitals and Clinics (2023-2034) ($MN)
  • Table 47 Global AI-Based Population Screening Market Outlook, By Diagnostic Centers (2023-2034) ($MN)
  • Table 48 Global AI-Based Population Screening Market Outlook, By Government and Public Health Agencies (2023-2034) ($MN)
  • Table 49 Global AI-Based Population Screening Market Outlook, By Research Institutes (2023-2034) ($MN)
  • Table 50 Global AI-Based Population Screening Market Outlook, By Healthcare Payers (2023-2034) ($MN)
  • Table 51 Global AI-Based Population Screening Market Outlook, By Corporate Wellness Providers (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.