세계의 병리학 분야 AI 시장 : 제공별, 신경망별, 기능별, 이용 사례별, 최종사용자별, 지역별 - 예측(-2030년)
Al in Pathology Market by Neural Network(GAN, CNN, RNN),Function(Diagnostic, Image Analysis, CDSS, Data Management, Analytics),Use Case(Drug Discovery, Clinical Workflow),End User(Hospitals, Labs, Pharma/Biotech), & Region-Global Forecast to 2030
상품코드:1728604
리서치사:MarketsandMarkets
발행일:2025년 05월
페이지 정보:영문 320 Pages
라이선스 & 가격 (부가세 별도)
ㅁ Add-on 가능: 고객의 요청에 따라 일정한 범위 내에서 Customization이 가능합니다. 자세한 사항은 문의해 주시기 바랍니다.
한글목차
세계 병리학 분야 AI 시장 규모는 예측 기간 동안 26.5%의 높은 CAGR로 확대되어 2025년 1억 743만 달러에서 2030년에는 3억 4,739만 달러에 달할 것으로 예상됩니다.
The Personalized Medicine Coalition Report 2022에 따르면, 2023년 FDA는 희귀질환 환자를 위한 16개의 새로운 맞춤형 치료제를 승인했습니다. 새로 승인된 치료법 중 7개의 암 치료제와 3개의 기타 질환 및 병태생리를 대상으로 하는 치료제가 있습니다. 승인된 맞춤형 치료제의 약 47%는 암 치료를 적응증으로 하고 있습니다.
조사 범위
조사 대상 연도
2024-2030년
기준 연도
2024년
예측 기간
2024-2030년
검토 단위
금액(10억 달러)
부문
제공별, 신경망별, 기능별, 사용 사례별, 최종사용자별, 지역별
대상 지역
북미, 유럽, 아시아태평양, 라틴아메리카, 중동 및 아프리카
2024년, 신약개발 부문은 병리학 분야 AI 시장에서 가장 큰 점유율을 차지했습니다. 제약 및 생명공학 R&D 비용의 증가, 고처리량 스크리닝 및 이미징의 증가, 질병 식별 및 분류를 위한 병리 영상 분석에서 AI 알고리즘의 사용 증가, 새로운 치료제 개발을 가속화하는 AI의 능력은 시장을 견인할 것으로 예상됩니다.
2024년 제약 및 바이오 제약 기업 부문은 신약 개발 및 시장 개척의 진전과 약독물 검사에서 병리학 분야 AI의 사용 증가로 인해 가장 큰 시장 점유율을 차지했습니다. 생명공학 기업들은 바이오뱅크, 바이오의약품 연구, 분자 분석, 맞춤형 의료 개발에 AI 기반 디지털 병리 검사를 활용하고 있습니다.
2024년 북미가 병리학 분야 Al 시장에서 가장 큰 시장 점유율을 차지한 것은 첨단 기계 사용을 가능하게 하는 연구 개발 및 첨단 의료 인프라에 대한 활발한 투자에 기인합니다. 대규모 환자 풀과 데이터의 가용성은 더 높은 정확도와 효율성을 위해 AI를 훈련시키는 데 사용할 수 있는 대규모 데이터베이스를 만드는 데 도움이 됩니다.
세계의 병리학 분야 AI 시장을 조사했으며, 제공별, 신경망별, 기능별, 사용 사례별, 최종사용자별, 지역별 동향, 시장 진입 기업 프로파일 등의 정보를 정리하여 전해드립니다.
목차
제1장 소개
제2장 조사 방법
제3장 주요 요약
제4장 주요 인사이트
제5장 시장 개요
소개
시장 역학
고객 비즈니스에 영향을 미치는 동향과 혼란
업계 동향
생태계 분석
밸류체인 분석
기술 분석
규제 상황
가격 분석
Porter's Five Forces 분석
특허 분석
주요 이해관계자와 구입 기준
최종사용자 분석
2025-2026년의 주요 회의와 이벤트
사례 연구 분석
투자와 자금 조달 시나리오
비즈니스 모델
병리학 분야 AI 시장에 대한 AI/GEN AI의 영향
무역 분석
미국의 2025년 관세
제6장 병리학 분야 AI 시장, 제공별
소개
엔드 투 엔드 솔루션
틈새 포인트 솔루션
테크놀러지
하드웨어
현미경
스캐너
스토리지 시스템
제7장 병리학 분야 AI 시장, 신경망별
소개
합성곱 신경망(CNNS)
적대적 생성 신경망(GANS)
순환 신경망(RNNS)
기타
제8장 병리학 분야 AI 시장, 기능별
소개
이미지 분석
진단
워크플로우 관리
데이터 관리
예측 분석
CDSS
자동 보고서 생성
품질 보증 툴
제9장 병리학 분야 AI 시장, 이용 사례별
소개
Drug Discovery
질병 진단과 예후
임상 워크플로우
트레이닝과 교육
제10장 병리학 분야 AI 시장, 최종사용자별
소개
제약회사 및 바이오의약품 회사
병원 및 검사기관
학술연구기관
제11장 병리학 분야 AI 시장, 지역별
소개
북미
거시경제 전망
미국
캐나다
유럽
거시경제 전망
영국
독일
프랑스
이탈리아
스페인
기타
아시아태평양
거시경제 전망
중국
일본
인도
기타
라틴아메리카
거시경제 전망
브라질
멕시코
기타
중동 및 아프리카
거시경제 전망
GCC 국가
기타
제12장 경쟁 구도
소개
주요 진출 기업 전략/강점
매출 분석, 2020-2024년
시장 점유율 분석, 2024년
기업 평가 매트릭스 : 주요 진출 기업, 2024년
기업 평가 매트릭스 : 스타트업/중소기업, 2024년
기업 평가와 재무 지표
브랜드/제품 비교
경쟁 시나리오
제13장 기업 개요
주요 진출 기업
KONINKLIJKE PHILIPS N.V.
F. HOFFMANN-LA ROCHE LTD.
HOLOGIC, INC.
AKOYA BIOSCIENCES, INC.
AIFORIA TECHNOLOGIES PLC
INDICA LABS INC.
OPTRASCAN
IBEX MEDICAL ANALYTICS LTD.
MINDPEAK GMBH
TRIBUN HEALTH
TECHCYTE, INC.
DEEP BIO INC.
LUMEA INC.
VISIOPHARM
AETHERAI
AIOSYN
PAIGE AI, INC.
PROSCIA, INC.
PATHAI, INC.
TEMPUS LABS, INC.
기타 기업
KONFOONG BIOINFORMATION TECH CO., LTD.
DOMORE DIAGNOSTICS AS
QRITIVE
DEEPATHOLOGY LTD
4D PATH INC.
제14장 부록
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영문 목차
영문목차
The global AI in pathology market is expected to reach USD 347.39 million by 2030 from USD 107.43 million in 2025 at a high CAGR of 26.5% during the forecast period. According to the Personalized Medicine Coalition Report 2022, in 2023, the FDA approved 16 new personalized treatments for patients with rare diseases. Among the newly approved treatments are seven cancer drugs and three targeting other diseases and conditions. About 47% of these approved personalized therapies were indicated for treating cancer.
Scope of the Report
Years Considered for the Study
2024-2030
Base Year
2024
Forecast Period
2024-2030
Units Considered
Value (USD billion)
Segments
Offering, Neural Network, Function, Use Case, End User
Regions covered
North America, Europe, Asia Pacific, Latin America, and Middle East & Africa
By use case, the drug discovery segment accounted for the largest share in 2024.
In 2024, the drug discovery segment accounted for the largest share of the AI in pathology market. Booming pharmaceutical & biotechnology R&D expenditure, the growing high-throughput screening & imaging, the increasing use of AI algorithms in pathology image analysis for the identification & classification of diseases, and the capability of AI to speed up the development of new therapeutics are expected to boost the market.
In 2024, the pharmaceutical & biopharmaceutical companies segment accounted for the largest share of the AI in pathology market, by end user.
In 2024, the pharmaceutical & biopharmaceutical companies segment accounted for the largest market share due to advancements in drug discovery & development and the increasing use of AI in pathology for drug toxicology testing. Biotechnology companies use AI-based digital pathology for biobanking, biopharmaceutical studies, molecular assays, and the development of individualized medicine.
North America held the largest market share in 2024.
In 2024, North America accounted for the largest market share in the AI in pathology market due to strong investment in research & development and advanced healthcare infrastructure, which enables the use of high-tech machinery. The large patient pool and data availability help create a large database, which can be used to train the AI for higher accuracy and efficiency.
The breakdown of primary participants is as mentioned below:
By Company Type - Tier 1: 45%, Tier 2: 30%, and Tier 3: 25%
By Designation - C-level: 42%, Director-level: 31%, and Others: 27%
By Region - North America: 32%, Europe: 32%, Asia Pacific: 26%, Middle East & Africa: 5%, Latin America: 5%
Key Players
The key players in the AI in pathology market include Koninklijke Philips N.V. (Netherlands), F. Hoffmann-La Roche Ltd (Switzerland), Hologic, Inc. (US), Akoya Biosciences, Inc. (US), Aiforia Technologies Plc (Finland), Indica Labs Inc. (US), OptraScan (US), Ibex Medical Analytics Ltd. (Israel).
Research Coverage
The report estimates the market size and future growth potential of various market segments based on offering, neural network, use case, end user, function, and region. It also provides a competitive analysis of the key players in this market, along with their company profiles, product offerings, recent developments, and key market strategies.
Reasons to Buy the Report
This report will enrich established firms and new entrants/smaller firms to gauge the market's pulse, which, in turn, would help them garner a higher share of the market. Firms purchasing the report could use one or a combination of the below-mentioned strategies to strengthen their positions in the market.
This report provides insights on:
Analysis of key drivers (development of CNNs and advanced AI models, Integration of AI into multiplex imaging, increasing cases of misdiagnoses in patients, benefits of AI-augmented telepathology, advancements in deep learning & image processing) restraints (high cost of digital pathology systems, limited AI expertise and varied regulatory guidelines for medical software, interoperability issues with legacy systems), opportunities (increasing demand for personalized medicine, integration of multi-omics data, and predictive analytics for disease progression) challenges (insufficient data for AI algorithms, data privacy, and ethical concerns, challenges associated with interpretability of AI models) influencing the growth of the AI in pathology market
Product Development/Innovation: Detailed insights into upcoming technologies, research & development activities, and new product & service launches in the AI in pathology market
Market Development: Comprehensive information on the lucrative emerging markets by offering, neural network, function, use case, end user, and region
Market Diversification: Exhaustive information about the product portfolios, growing geographies, recent developments, and investments in the market
Competitive Assessment: In-depth assessment of market shares, growth strategies, product offerings, and capabilities of the leading players
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKET SEGMENTATION AND GEOGRAPHIC SPREAD
1.3.2 INCLUSIONS & EXCLUSIONS
1.4 YEARS CONSIDERED
1.5 CURRENCY CONSIDERED
1.6 KEY STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.1.1 Key data from secondary sources
2.1.2 PRIMARY DATA
2.1.2.1 Revenue share analysis illustration
2.2 MARKET SIZE ESTIMATION
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
2.5 RESEARCH LIMITATIONS
2.5.1 METHODOLOGY-RELATED LIMITATIONS
2.5.2 SCOPE-RELATED LIMITATIONS
2.6 RISK ASSESSMENT
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 KEY OPPORTUNITIES FOR PLAYERS IN AI IN PATHOLOGY MARKET
4.2 AI IN PATHOLOGY MARKET: REGIONAL MIX
4.3 ASIA PACIFIC: AI IN PATHOLOGY MARKET, BY END USER AND KEY COUNTRY/REGION
4.4 GEOGRAPHIC GROWTH OPPORTUNITIES
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Development of CNNs and advanced AI models
5.2.1.2 Integration of AI into multiplex imaging
5.2.1.3 Increasing cases of misdiagnoses in patients
5.2.1.4 Benefits of AI-augmented telepathology
5.2.1.5 Advancements in deep learning & image processing
5.2.2 RESTRAINTS
5.2.2.1 High cost of digital pathology systems
5.2.2.2 Limited AI expertise and varied regulatory guidelines for medical software
5.2.2.3 Inadequate interoperability issues with legacy systems
5.2.3 OPPORTUNITIES
5.2.3.1 Increasing demand for personalized medicines
5.2.3.2 Integration of multi-omics data
5.2.3.3 Predictive analytics for disease progression
5.2.4 CHALLENGES
5.2.4.1 Insufficient data for AI algorithms
5.2.4.2 Data privacy and ethical concerns
5.2.4.3 Challenges associated with interpretability of AI models
5.3 TRENDS & DISRUPTIONS IMPACTING CUSTOMER BUSINESS
5.4 INDUSTRY TRENDS
5.4.1 EVOLUTION OF AI IN PATHOLOGY
5.5 ECOSYSTEM ANALYSIS
5.6 VALUE CHAIN ANALYSIS
5.7 TECHNOLOGY ANALYSIS
5.7.1 KEY TECHNOLOGIES
5.7.1.1 Machine learning (ML) and artificial intelligence (AI)
5.7.1.2 Computer vision
5.7.2 COMPLEMENTARY TECHNOLOGIES
5.7.2.1 Cloud computing
5.7.3 ADJACENT TECHNOLOGIES
5.7.3.1 Telepathology
5.8 REGULATORY LANDSCAPE
5.8.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.8.2 REGULATIONS, BY REGION
5.8.2.1 North America
5.8.2.1.1 US
5.8.2.1.2 Canada
5.8.2.2 Europe
5.8.2.3 Asia Pacific
5.8.2.3.1 Japan
5.8.2.3.2 China
5.9 PRICING ANALYSIS
5.9.1 AVERAGE SELLING PRICE TREND, BY REGION
5.9.2 INDICATIVE PRICING ANALYSIS, BY OFFERING
5.10 PORTER'S FIVE FORCES ANALYSIS
5.10.1 THREAT FROM NEW ENTRANTS
5.10.2 THREAT FROM SUBSTITUTES
5.10.3 BARGAINING POWER OF SUPPLIERS
5.10.4 BARGAINING POWER OF BUYERS
5.10.5 INTENSITY OF COMPETITIVE RIVALRY
5.11 PATENT ANALYSIS
5.11.1 PATENT PUBLICATION TRENDS FOR AI IN PATHOLOGY SOLUTIONS
5.11.2 JURISDICTION AND TOP APPLICANT ANALYSIS
5.12 KEY STAKEHOLDERS AND BUYING CRITERIA
5.12.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.12.2 BUYING CRITERIA
5.13 END USER ANALYSIS
5.13.1 UNMET NEEDS OF END USERS
5.13.2 END USER EXPECTATIONS
5.14 KEY CONFERENCES AND EVENTS, 2025-2026
5.15 CASE STUDY ANALYSIS
5.15.1 CASE STUDY 1: PATBAL EMPLOYED PYTORCH FOR ITS HIGH-LEVEL PYTHONIC SYNTAX TO SUPPORT DIVERSE MODELING APPROACHES
5.15.2 CASE STUDY 2: KFBIO DEVELOPED KFBIO AI CERVICAL CANCER SCREENING SYSTEM TO STRENGTHEN CANCER DIAGNOSIS
5.15.3 CASE STUDY 3: RESEARCH TEAM FROM UNIVERSITY OF HELSINKI USED AIFORIA CREATE TO DEVELOP DEEP-LEARNING AI MODEL TO PREDICT PATIENT OUTCOMES
5.16 INVESTMENT & FUNDING SCENARIO
5.17 BUSINESS MODELS
5.18 IMPACT OF AI/GEN AI ON AI IN PATHOLOGY MARKET
5.18.1 KEY USE CASES
5.18.2 AI/GENERATIVE AI IMPLEMENTATION: CASE STUDY
5.18.2.1 Accelerated biomarker discovery and clinical trial optimization
5.18.3 IMPACT OF AI/GEN AI ON INTERCONNECTED AND ADJACENT ECOSYSTEMS
5.18.3.1 Drug discovery & development market
5.18.3.2 Medical imaging & diagnostics market
5.18.4 USER READINESS AND IMPACT ASSESSMENT
5.18.4.1 User readiness
5.18.4.1.1 Pharmaceutical companies
5.18.4.1.2 Biopharmaceutical companies
5.18.4.2 Impact assessment
5.18.4.2.1 User A: Pharmaceutical companies
5.18.4.2.1.1 Implementation
5.18.4.2.1.2 Impact
5.18.4.2.2 User B: Biopharmaceutical companies
5.18.4.2.2.1 Implementation
5.18.4.2.2.2 Impact
5.19 TRADE ANALYSIS
5.19.1 IMPORT SCENARIO
5.19.2 EXPORT SCENARIO
5.20 US 2025 TARIFF
5.20.1 INTRODUCTION
5.20.2 KEY TARIFF RATES
5.20.3 PRICE IMPACT ANALYSIS
5.20.4 IMPACT ON COUNTRY/REGION
5.20.4.1 US
5.20.4.2 Europe
5.20.4.3 Asia Pacific
5.20.5 IMPACT ON END USE INDUSTRIES
6 AI IN PATHOLOGY MARKET, BY OFFERING
6.1 INTRODUCTION
6.2 END-TO-END SOLUTIONS
6.2.1 INCREASING DEMAND FOR INTEGRATED WORKFLOWS IN HEALTHCARE MODELS TO DRIVE MARKET
6.3 NICHE POINT SOLUTIONS
6.3.1 GROWING FOCUS ON PRECISION MEDICINE AND TARGETED THERAPY RESEARCH TO PROPEL MARKET
6.4 TECHNOLOGY
6.4.1 RISING NEED FOR ADVANCED DATA MANAGEMENT SOLUTIONS TO FUEL MARKET
6.5 HARDWARE
6.5.1 HIGH ADOPTION OF AI-BASED MICROSCOPES TO PROPEL MARKET
6.6 MICROSCOPES
6.6.1 NEED FOR AUTOMATED ANALYSIS OF TISSUE SAMPLES TO FUEL GROWTH
6.7 SCANNERS
6.7.1 IMPROVEMENTS IN IMAGE QUALITY AND PRECISION DIAGNOSTICS TO BOOST DEMAND
6.8 STORAGE SYSTEMS
6.8.1 NEED FOR STRUCTURED MODELS OF HIGH-RESOLUTION IMAGES TO SUPPORT MARKET GROWTH
7 AI IN PATHOLOGY MARKET, BY NEURAL NETWORK
7.1 INTRODUCTION
7.2 CONVOLUTIONAL NEURAL NETWORKS (CNNS)
7.2.1 FOCUS ON PROVIDING HIGH-QUALITY IMAGE RECOGNITION AND OBJECTION DETECTION TO PROPEL MARKET
7.3 GENERATIVE ADVERSARIAL NETWORKS (GANS)
7.3.1 NEED FOR GENERATING ACCURATE SYNTHETIC PATHOLOGY IMAGES TO DRIVE MARKET
7.4 RECURRENT NEURAL NETWORKS (RNNS)
7.4.1 NEED FOR ANALYSIS OF SEQUENTIAL DATA AND TIME-DEPENDENT PATTERNS TO FUEL MARKET
7.5 OTHER NEURAL NETWORKS
8 AI IN PATHOLOGY MARKET, BY FUNCTION
8.1 INTRODUCTION
8.2 IMAGE ANALYSIS
8.2.1 DETECTION OF CELLULAR ANOMALIES AND DISEASE MARKERS TO FUEL UPTAKE
8.3 DIAGNOSTICS
8.3.1 RAPID PROCESSION OF AUTOMATED SAMPLES TO DRIVE MARKET
8.4 WORKFLOW MANAGEMENT
8.4.1 OPTIMIZATION OF LAB RESOURCES FOR HIGH-THROUGHPUT RESULTS TO FUEL UPTAKE
8.5 DATA MANAGEMENT
8.5.1 EMPHASIS ON ADVANCEMENTS IN DATA INTEGRATION AND PROCESSING TO BOOST DEMAND
8.6 PREDICTIVE ANALYTICS
8.6.1 GROWING FOCUS ON EARLY DIAGNOSIS OF DISEASES TO DRIVE MARKET
8.7 CDSS
8.7.1 PROVISION OF REAL-TIME INSIGHTS TO FUEL MARKET
8.8 AUTOMATED REPORT GENERATION
8.8.1 INCREASING DEMAND FOR QUALITY CONTROL TO DRIVE MARKET
8.9 QUALITY ASSURANCE TOOLS
8.9.1 RISING REGULATORY NEED TO ACCELERATE DEMAND FOR QUALITY ASSURANCE TOOLS TO BOOST GROWTH
9 AI IN PATHOLOGY MARKET, BY USE CASE
9.1 INTRODUCTION
9.2 DRUG DISCOVERY
9.2.1 TARGET IDENTIFICATION & SELECTION
9.2.1.1 Analysis of molecular and histological data for biomarker discovery to fuel market
9.2.2 TARGET VALIDATION
9.2.2.1 Increasing demand for precision medicines to drive market
9.2.3 HIT IDENTIFICATION & PRIORITIZATION
9.2.3.1 Growing requirement for rapid analysis and cost efficiency to fuel uptake
9.2.4 HIT-TO-LEAD IDENTIFICATION
9.2.4.1 Advancements in ML to support market growth
9.2.5 LEAD OPTIMIZATION
9.2.5.1 Growing focus on therapeutic efficacy to propel market
9.2.6 CANDIDATE SELECTION & VALIDATION
9.2.6.1 Critical requirement for regulatory approvals to drive market
9.3 DISEASE DIAGNOSIS & PROGNOSIS
9.3.1 INCREASING INCIDENCE OF CHRONIC DISEASES TO FUEL MARKET
9.4 CLINICAL WORKFLOW
9.4.1 STRUCTURED AUTOMATION OF EXTENSIVE VOLUME DATA TO DRIVE MARKET
9.5 TRAINING & EDUCATION
9.5.1 UTILIZATION OF DIGITAL PATHOLOGY SYSTEMS IN ACADEMIC INSTITUTES TO SUPPORT MARKET GROWTH
10 AI IN PATHOLOGY MARKET, BY END USER
10.1 INTRODUCTION
10.2 PHARMACEUTICAL & BIOPHARMACEUTICAL COMPANIES
10.2.1 GROWING FOCUS ON TOXICOLOGY TESTING TO PROPEL MARKET
10.3 HOSPITALS & REFERENCE LABORATORIES
10.3.1 INCREASING NEED FOR EFFECTIVE DIAGNOSES OF INFECTIOUS DISEASES TO DRIVE GROWTH
10.4 ACADEMIC & RESEARCH INSTITUTES
10.4.1 GROWING INVESTMENTS IN LIFE SCIENCES RESEARCH TO SUPPORT DEMAND
11 AI IN PATHOLOGY MARKET, BY REGION
11.1 INTRODUCTION
11.2 NORTH AMERICA
11.2.1 MACROECONOMIC OUTLOOK
11.2.2 US
11.2.2.1 High healthcare expenditure and improvements in cloud computing platforms to propel market
11.2.3 CANADA
11.2.3.1 Increasing adoption of deep learning for advanced healthcare diagnostics to drive market
11.3 EUROPE
11.3.1 MACROECONOMIC OUTLOOK
11.3.2 UK
11.3.2.1 Increased focus on drug discovery and development to boost demand
11.3.3 GERMANY
11.3.3.1 Availability of funding for AI initiatives to fuel uptake
11.3.4 FRANCE
11.3.4.1 Increasing adoption of big data in healthcare computing to fuel uptake
11.3.5 ITALY
11.3.5.1 Digital transformation and innovation in healthcare to support market growth
11.3.6 SPAIN
11.3.6.1 Increased workforce shortage to fuel market
11.3.7 REST OF EUROPE
11.4 ASIA PACIFIC
11.4.1 MACROECONOMIC OUTLOOK
11.4.2 CHINA
11.4.2.1 Rising cases of infectious and chronic diseases to fuel demand
11.4.3 JAPAN
11.4.3.1 Advanced healthcare infrastructure to propel market
11.4.4 INDIA
11.4.4.1 Growing focus on healthcare digitization to boost demand
11.4.5 REST OF ASIA PACIFIC
11.5 LATIN AMERICA
11.5.1 MACROECONOMIC OUTLOOK
11.5.2 BRAZIL
11.5.2.1 Strategic investments for AI adoption to support market growth
11.5.3 MEXICO
11.5.3.1 Growth in pharmaceutical R&D to drive market
11.5.4 REST OF LATIN AMERICA
11.6 MIDDLE EAST & AFRICA
11.6.1 MACROECONOMIC OUTLOOK
11.6.2 GCC COUNTRIES
11.6.2.1 Increasing investments for expansion of technological expertise to support growth
11.6.3 REST OF MIDDLE EAST & AFRICA
12 COMPETITIVE LANDSCAPE
12.1 INTRODUCTION
12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
12.2.1 OVERVIEW OF STRATEGIES ADOPTED BY PLAYERS IN AI IN PATHOLOGY MARKET
12.3 REVENUE ANALYSIS, 2020-2024
12.4 MARKET SHARE ANALYSIS, 2024
12.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
12.5.1 STARS
12.5.2 EMERGING LEADERS
12.5.3 PERVASIVE PLAYERS
12.5.4 PARTICIPANTS
12.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
12.5.5.1 Company footprint
12.5.5.2 Offering footprint
12.5.5.3 Use case footprint
12.5.5.4 End user footprint
12.5.5.5 Region footprint
12.6 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
