머신러닝/AI 진단 시장 예측(-2032년) : 구성 요소별, 진단 유형별, 기술별, 용도별, 최종 사용자별, 지역별 세계 분석

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