세계의 헬스케어 분야 인공지능(AI) 시장 : 제공별, 기능별, 용도별, 전개 방식별, 툴별, 최종사용자별, 지역별 - 예측(-2030년)
Artificial Intelligence(AI) in Healthcare Market by Offering(Integrated), Function(Diagnosis, Genomic, Precision Medicine, Radiation, Immunotherapy, Pharmacy, Supply Chain), Application(Clinical), End User(Hospitals), Region-Global Forecast to 2030
상품코드:1728616
리서치사:MarketsandMarkets
발행일:2025년 05월
페이지 정보:영문 713 Pages
라이선스 & 가격 (부가세 별도)
ㅁ Add-on 가능: 고객의 요청에 따라 일정한 범위 내에서 Customization이 가능합니다. 자세한 사항은 문의해 주시기 바랍니다.
한글목차
세계 헬스케어 분야 인공지능(AI) 시장 규모는 2025년 216억 6,000만 달러에서 2030년 1,106억 1,000만 달러에 달할 것으로 예상되며, 예측 기간 동안 38.6%의 CAGR을 기록할 것으로 예상됩니다.
이 시장은 민관 조직의 투자 및 자금 조달 증가, 헬스케어 산업에서 AI의 급속한 보급, 인간을 의식한 AI 시스템 개발에 대한 관심 증가로 인해 성장이 예상됩니다. 이 시장은 의료 인력 대비 환자 수의 불균형한 비율로 인해 더 나은 서비스에 대한 수요가 증가함에 따라 성장하고 있습니다. 그러나 신흥국의 경우 IT 인프라가 부족하고 AI 기반 헬스케어 솔루션 도입에 소극적인 점이 시장 성장의 걸림돌로 작용할 것으로 추정됩니다.
조사 범위
조사 대상 연도
2024-2030년
기준 연도
2024년
예측 기간
2024-2030년
검토 단위
금액(10억 달러)
부문
제공별, 기능별, 용도별, 전개 방식별, 툴별, 최종사용자별, 지역별
대상 지역
북미, 유럽, 아시아태평양, 라틴아메리카, 중동 및 아프리카
헬스케어 AI 시장은 온프레미스, 클라우드 기반, 하이브리드 모델의 세 가지 전개 모델로 분류됩니다. 클라우드 기반 모델은 확장성, 비용 효율성, 접근 용이성으로 인해 가장 큰 점유율을 차지하고 있습니다. 클라우드 기반 모델은 실시간 데이터 처리와 협업을 용이하게 합니다. 원활한 통합, 안전한 데이터 저장, 빠른 배포가 가능하기 때문에 특히 의료 서비스 제공자 및 지불자에게 적합합니다. 고품질 표준을 유지하면서 보다 신속하고 신뢰할 수 있는 의료 서비스를 제공합니다. 클라우드 기반 AI 솔루션은 비용 효율성, 확장성 및 원격 액세스 지원으로 인해 점점 더 많은 인기를 얻고 있습니다. 이러한 솔루션은 원활한 통합과 실시간 분석을 가능하게 합니다. 원격의료의 확산과 헬스케어 IT 인프라의 발전은 클라우드 기반 모델에 대한 수요를 더욱 증가시키고 있습니다.
최종사용자별로 헬스케어 인공지능(AI) 시장은 병원 및 클리닉, 외래 수술 센터, 재택의료기관 및 복지시설, 진단 및 영상 진단센터, 약국, 기타 헬스케어 제공업체로 구분됩니다. 헬스케어 인공지능(AI) 시장에서는 병원 및 클리닉 분야가 가장 큰 비중을 차지하고 있습니다. AI 기반 헬스케어 솔루션은 병원 및 클리닉에서 진단 정확도를 높이고, 업무를 간소화하며, 병원 및 클리닉의 관리를 자동화하고, 관리 업무를 자동화하며, 환자 맞춤형 치료를 가능하게 합니다. AI는 관리 업무를 자동화하고, 환자 결과를 예측하며, 실시간 데이터 분석을 통해 신속한 의사결정을 내릴 수 있도록 돕고, 원격 모니터링을 지원하고, 자원을 최적화하고, 불필요한 치료를 최소화하여 비용을 절감할 수 있습니다. 환자 참여를 향상시키고, 부정행위를 감지하여 보안을 강화하며, 의료 서비스를 보다 효율적이고 접근성이 높으며, 비용 효율적으로 만듭니다.
헬스케어 분야 인공지능(AI) 시장은 북미, 유럽, 아시아태평양, 라틴아메리카, 중동 및 아프리카로 나뉘어져 있습니다. 아시아태평양은 예측 기간 동안 가장 높은 성장률을 기록할 것으로 예상됩니다. 아시아태평양은 인구통계학적 변화, 기술 발전, 혁신에 대한 투자 증가로 인해 헬스케어 분야에서 AI 기술 채택이 크게 증가하고 있습니다. 아시아태평양의 노인 인구 증가는 중요한 요인으로, 65세 이상 노인의 비율이 크게 증가하고 있습니다. 유엔의 '세계 인구 고령화 2020' 보고서에 따르면 이 연령대의 세계 인구는 2020년 7억 2,700만 명에서 2050년 15억 명으로 두 배로 증가할 것으로 예상되며, 그 중 동아시아와 동남아시아가 큰 비중을 차지할 것으로 예상됩니다.
세계의 헬스케어 분야 인공지능(AI) 시장에 대해 조사했으며, 제공별, 기능별, 용도별, 전개 방식별, 도구별, 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
고객의 비즈니스에 영향을 미치는 동향/혼란
기술 분석
업계 동향
가격 분석
밸류체인 분석
생태계 분석
특허 분석
주요 회의와 이벤트
사례 연구 분석
규제 상황
Porter's Five Forces 분석
주요 이해관계자와 구입 기준
최종사용자 분석
헬스케어 비즈니스 모델의 AI
투자와 자금 조달 시나리오
생성형 AI가 헬스케어 시장의 AI에 미치는 영향
제6장 2025년 미국 관세의 영향 - 개요
소개
주요 관세율
가격 영향 분석
국가/지역에 대한 영향
최종 이용 산업에 대한 영향
제7장 헬스케어 분야 인공지능(AI) 시장, 제공별
소개
통합 솔루션
틈새/포인트 솔루션
AI 테크놀러지
서비스
제8장 헬스케어 분야 인공지능(AI) 시장, 기능별
소개
진단과 조기 발견
치료 계획과 개인화
환자 참여와 원격 모니터링
치료 후 감시와 생존자 케어
약국 경영
데이터 관리와 분석
행정
제9장 헬스케어 분야 인공지능(AI) 시장, 용도별
소개
임상
비임상
제10장 헬스케어 분야 인공지능(AI) 시장, 전개 방식별
소개
온프레미스 모델
클라우드 기반 모델
하이브리드 모델
제11장 헬스케어 분야 인공지능(AI) 시장, 툴별
소개
머신러닝
자연어 처리(NLP)
상황인식 컴퓨팅
생성형 AI
컴퓨터 비전
이미지 분석
제12장 헬스케어 분야 인공지능(AI) 시장, 최종사용자별
소개
의료 제공자
의료 지불자
환자
기타
제13장 헬스케어 분야 인공지능(AI) 시장, 지역별
소개
북미
북미의 거시경제 전망
미국
캐나다
유럽
유럽의 거시경제 전망
독일
영국
프랑스
이탈리아
스페인
기타
아시아태평양
아시아태평양의 거시경제 전망
중국
일본
인도
기타
라틴아메리카
라틴아메리카의 거시경제 전망
브라질
멕시코
기타
중동 및 아프리카
중동 및 아프리카의 거시경제 전망
GCC 국가
기타
제14장 경쟁 구도
소개
주요 진출 기업 전략/강함
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
제15장 기업 개요
주요 진출 기업
KONINKLIJKE PHILIPS N.V.
MICROSOFT CORPORATION
NVIDIA CORPORATION
SIEMENS HEALTHINEERS AG
GE HEALTHCARE
EPIC SYSTEMS CORPORATION
ORACLE CORPORATION
VERADIGM INC.
AMAZON WEB SERVICES, INC.
MERATIVE
IBM
MEDTRONIC
GOOGLE
SOPHIA GENETICS
JOHNSON & JOHNSON SERVICES, INC.
TEMPUS AI, INC.
CONCERTAI
SOLVENTUM CORPORATION
COGNIZANT
VIZ.AI, INC.
RIVERAIN TECHNOLOGIES
기타 기업
QVENTUS
QURE.AI
ATOMWISE INC.
ENLITIC
SEGMED
제16장 부록
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영문 목차
영문목차
The global Artificial Intelligence (AI) in healthcare market is projected to reach USD 110.61 billion by 2030 from USD 21.66 billion in 2025, at a CAGR of 38.6% during the forecast period. The market is expected to grow due to the growing investments & funding by public-private organizations, the fast proliferation of AI in the healthcare industry, and the rising focus on developing human-aware AI systems. The market has experienced growth due to increasing demand for enhanced services due to an unequal ratio between the healthcare workforce and patient numbers. However, inadequate IT infrastructure and unwillingness to adopt AI-based healthcare solutions in emerging economies are estimated to pose a challenge to market growth.
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, Function, Application, Deployment, Tools, End User
Regions covered
North America, Europe, Asia Pacific, Latin America, and Middle East & Africa
By deployment, the cloud-based segment is expected to register the highest growth during the forecast period.
The AI in healthcare market is categorized into three deployment models: on-premise, cloud-based, and hybrid models. The cloud-based models segment holds the largest share due to the scalability, cost-effectiveness, and accessibility of these models. Cloud-based models facilitate real-time data processing and collaboration. They allow for seamless integration, secure data storage, and rapid deployment, making them particularly suitable for healthcare providers and payers. They provide faster, more reliable care while maintaining high-quality standards. Cloud-based AI solutions are becoming increasingly popular due to their cost-effectiveness, scalability, and support for remote access. These solutions enable seamless integration and real-time analytics. The growing adoption of telehealth and advancements in healthcare IT infrastructure further drive the demand for cloud-based models.
By end user, the hospitals & clinics segment dominated the market in the Artificial Intelligence (AI) in healthcare market for healthcare providers in 2024.
By end user, Artificial Intelligence (AI) in healthcare market is segmented into hospitals & clinics, ambulatory surgical centers, home healthcare agencies & assisted living facilities, diagnostic & imaging centers, pharmacies, and other healthcare providers. The hospitals & clinics segment accounted for the largest share of the Artificial Intelligence (AI) in healthcare market. This is attributed to the increasing demand for personalized medicines, precise diagnostics & surgical planning, growth in minimally-invasive procedures, and the requirement for interoperability with existing systems. AI-based healthcare solutions enhance diagnostic accuracy, streamline operations, and personalize care in hospitals and clinics. They automate administrative tasks, predict patient outcomes, and enable faster decision-making with real-time data analysis. AI also supports remote monitoring, optimizes resources, and reduces costs by minimizing unnecessary treatments. AI improves patient engagement through virtual assistants and enhances security by detecting fraud, making healthcare more efficient, accessible, and cost-effective.
Asia Pacific is expected to register the highest growth during the forecast period.
The Artificial Intelligence (AI) in healthcare market is divided into North America, Europe, Asia Pacific, Latin America, and Middle East & Africa. The Asia Pacific region is expected to register the highest growth during the forecast period. The Asia Pacific (APAC) region is experiencing substantial growth in the adoption of AI technologies within the healthcare sector, driven by a combination of demographic shifts, technological advancements, and increased investments in innovation. The rising elderly population in the Asia Pacific is a key factor, with the proportion of individuals aged 65 years and above increasing significantly. According to the UN's World Population Aging 2020 report, the global population in this age group is expected to double from 727 million in 2020 to 1.5 billion by 2050, with Eastern and Southeastern Asia contributing a large share of this growth.
The break-down of primary participants is as mentioned below:
By Company Type - Tier 1: 32%, Tier 2: 44%, and Tier 3: 24%
By Designation - Directors: 30%, Manager: 34%, and Others: 36%
By Region - North America: 40%, Europe: 28%, Asia Pacific: 20%, Latin America: 7% and Middle East & Africa: 5%
Key Players
The prominent players operating in the Artificial Intelligence (AI) in healthcare market include Koninklijke Philips N.V. (Netherlands), Microsoft Corporation (US), Siemens Healthineers AG (Germany), NVIDIA Corporation (US), Epic Systems Corporation (US), GE Healthcare (US), Medtronic (US), Oracle (US), Veradigm LLC (US), Merative (IBM) (US), Google (US), Cognizant (US), Johnson & Johnson (US), Amazon Web Services, Inc. (US), SOPHiA GENETICS (US), Riverian Technologies (US), Terarecon (ConcertAI) (US), Solventum Corporation (US), Tempus (US), Viz.ai (US). These companies adopted strategies such as product launches, product updates, expansions, partnerships, collaborations, mergers, and acquisitions to strengthen their market presence in the Artificial Intelligence (AI) in healthcare market.
Research Coverage
The report analyzes the Artificial Intelligence (AI) in healthcare market and aims to estimate the market size and future growth potential of various market segments based on offering, solution type, imaging modality, application, end user, and region. The report also analyzes factors (such as drivers, opportunities, and challenges) affecting market growth. It evaluates the opportunities and challenges in the market stakeholders. The report also studies micro markets with respect to their growth trends, prospects, and contributions to the total Artificial Intelligence (AI) in healthcare market. The report forecasts the revenue of the market segments with respect to five major regions. The report 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 as well as new entrants/smaller firms to gauge the pulse of the market, which, in turn, would help them garner a higher market share. Firms purchasing the report could use one or a combination of the following strategies to strengthen their positions in the market.
This report provides insights on:
Analysis of key drivers (exponential growth in data volume and complexity due to surging adoption of digital technologies, significant cost pressure on healthcare service providers with increasing prevalence of chronic diseases, rapid proliferation of AI in healthcare sector, growing need for improvised healthcare services, growing need for early detection and diagnosis, restraints (reluctance among medical practitioners to adopt AI-based technologies, shortage of skilled AI professionals handling AI-powered solutions, lack of standardized frameworks for AI and ML technologies), opportunities (increasing use of AI-powered solutions in elderly care, increasing focus on developing human-aware AI systems, strategic partnerships and collaborations among healthcare companies and AI technology providers), challenges (inaccurate predictions due to scarcity of high-quality healthcare data, concerns regarding data privacy, lack of interoperability between AI solutions offered by different vendors) are factors contributing the growth of the Artificial Intelligence (AI) in healthcare market
Product Development/Innovation: Detailed insights into upcoming trends, research & development activities, and software launches in the Artificial Intelligence (AI) in healthcare market
Market Development: Comprehensive information on the lucrative emerging markets, type of solution, component, deployment model, industry, and region
Market Diversification: Exhaustive information about software portfolios, growing geographies, recent developments, and investments in the Artificial Intelligence (AI) in healthcare market
Competitive Assessment: In-depth assessment of market shares, growth strategies, product offerings, company evaluation quadrant, and capabilities of leading players in the global Artificial Intelligence (AI) in healthcare market, such as Koninklijke Philips N.V. (Netherlands), Microsoft Corporation (US), Siemens Healthineers AG (Germany), NVIDIA Corporation (US), Epic Systems Corporation (US)
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED
1.3.2 INCLUSIONS & EXCLUSIONS
1.3.3 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 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 Key industry insights
2.2 MARKET SIZE ESTIMATION
2.3 DATA TRIANGULATION
2.4 MARKET SHARE ESTIMATION
2.5 STUDY ASSUMPTIONS
2.6 LIMITATIONS
2.6.1 METHODOLOGY-RELATED LIMITATIONS
2.6.2 SCOPE-RELATED LIMITATIONS
2.7 RISK ASSESSMENT
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 AI IN HEALTHCARE MARKET OVERVIEW
4.2 ASIA PACIFIC: AI IN HEALTHCARE, BY OFFERING AND COUNTRY
4.3 AI IN HEALTHCARE MARKET: GEOGRAPHIC GROWTH OPPORTUNITIES
4.4 AI IN HEALTHCARE MARKET: REGIONAL MIX
4.5 AI IN HEALTHCARE: DEVELOPED VS. EMERGING MARKETS
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Increase in need for early detection and diagnosis
5.2.1.2 Exponential growth in data volume and complexity due to surging adoption of digital technologies
5.2.1.3 Significant cost pressure on healthcare service providers with increasing prevalence of chronic diseases
5.2.1.4 Rapid proliferation of AI in healthcare sector
5.2.1.5 Growth in need for improvised healthcare services
5.2.2 RESTRAINTS
5.2.2.1 Reluctance among medical practitioners to adopt AI-based technologies
5.2.2.2 Shortage of skilled AI professionals handling AI-powered solutions
5.2.2.3 Lack of standardized frameworks for AI and ML technologies
5.2.3 OPPORTUNITIES
5.2.3.1 Increasing use of AI-powered solutions in elderly care
5.2.3.2 Increase in focus on developing human-aware AI systems
5.2.3.3 Strategic partnerships and collaborations among healthcare companies and AI technology providers
5.2.4 CHALLENGES
5.2.4.1 Inaccurate predictions due to scarcity of high-quality healthcare data
5.2.4.2 Concerns regarding data privacy
5.2.4.3 Lack of interoperability between AI solutions offered by different vendors
5.6.1 INDICATIVE PRICING OF AI IN HEALTHCARE SOFTWARE, BY DEPLOYMENT MODEL (QUALITATIVE)
5.6.2 INDICATIVE PRICING OF AI IN HEALTHCARE SOFTWARE, BY REGION (QUALITATIVE)
5.7 VALUE CHAIN ANALYSIS
5.8 ECOSYSTEM ANALYSIS
5.9 PATENT ANALYSIS
5.9.1 INSIGHTS: JURISDICTION AND TOP APPLICANT ANALYSIS
5.10 KEY CONFERENCES & EVENTS
5.11 CASE STUDY ANALYSIS
5.11.1 BIOBEAT LAUNCHED HOME-BASED REMOTE PATIENT MONITORING KIT DURING PEAK WAVE OF COVID-19
5.11.2 MICROSOFT COLLABORATED WITH CLEVELAND CLINIC TO APPLY PREDICTIVE AND ADVANCED ANALYTICS TO IDENTIFY POTENTIAL AT-RISK PATIENTS UNDER ICU CARE
5.11.3 TGEN COLLABORATED WITH INTEL CORPORATION AND DELL TECHNOLOGIES TO ASSIST PHYSICIANS AND RESEARCHERS IN ACCELERATING DIAGNOSIS AND TREATMENT AT LOWER COSTS
5.11.4 GE HEALTHCARE IMPROVED PATIENT OUTCOMES BY REDUCING WORKFLOW PROCESSING TIME USING MEDICAL IMAGING DATA
5.12 REGULATORY LANDSCAPE
5.12.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.12.2 REGULATORY FRAMEWORK
5.12.2.1 North America
5.12.2.2 Europe
5.12.2.3 Asia Pacific
5.12.2.4 Middle East & Africa
5.12.2.5 Latin America
5.13 PORTER'S FIVE FORCES ANALYSIS
5.13.1 THREAT OF NEW ENTRANTS
5.13.2 THREAT OF SUBSTITUTES
5.13.3 BARGAINING POWER OF SUPPLIERS
5.13.4 BARGAINING POWER OF BUYERS
5.13.5 INTENSITY OF COMPETITIVE RIVALRY
5.14 KEY STAKEHOLDERS & BUYING CRITERIA
5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.14.2 BUYING CRITERIA
5.15 END-USER ANALYSIS
5.15.1 UNMET NEEDS
5.15.2 END-USER EXPECTATIONS
5.16 AI IN HEALTHCARE BUSINESS MODELS
5.16.1 SOFTWARE-AS-A-SERVICE (SAAS) MODEL
5.16.2 LICENSING MODEL
5.16.3 REVENUE SHARING/OUTCOME-BASED MODEL
5.16.4 FREEMIUM MODEL
5.16.5 AI-AS-A-SERVICE (AIAAS) MODEL
5.16.6 PARTNERSHIP/REVENUE-SHARING MODEL
5.16.7 HYBRID MODELS
5.16.8 PAY-PER-USE MODELS
5.17 INVESTMENT & FUNDING SCENARIO
5.18 IMPACT OF GENERATIVE AI ON AI IN HEALTHCARE MARKET
5.18.1 INTRODUCTION
5.18.2 MARKET POTENTIAL OF GEN AI IN HEALTHCARE
5.18.2.1 Key use cases of Gen AI
5.18.3 CASE STUDIES OF AI/GENERATIVE AI IMPLEMENTATION
5.18.3.1 Eka Care leveraging generative AI for improved health outcomes
5.18.4 INTERCONNECTED AND ADJACENT ECOSYSTEMS
5.18.4.1 AI in healthcare IT
5.18.4.2 AI in medical diagnostics
5.18.4.3 AI in oncology
5.18.4.4 AI in clinical trials
5.18.4.5 AI in drug discovery
5.18.5 USER READINESS & IMPACT ASSESSMENT
5.18.5.1 User readiness
5.18.5.1.1 Healthcare providers
5.18.5.1.2 Healthcare payers
5.18.5.1.3 Patients
5.18.5.2 Impact assessment
5.18.5.2.1 User A: Healthcare providers
5.18.5.2.1.1 Implementation
5.18.5.2.1.2 Impact
5.18.5.2.2 User B: Healthcare payers
5.18.5.2.2.1 Implementation
5.18.5.2.2.2 Impact
5.18.5.2.3 User C: Patients
5.18.5.2.3.1 Implementation
5.18.5.2.3.2 Impact
6 IMPACT OF 2025 US TARIFF - OVERVIEW
6.1 INTRODUCTION
6.2 KEY TARIFF RATES
6.3 PRICE IMPACT ANALYSIS
6.4 IMPACT ON COUNTRY/REGION
6.4.1 US
6.4.2 EUROPE
6.4.3 ASIA PACIFIC
6.5 IMPACT ON END-USE INDUSTRIES
7 AI IN HEALTHCARE MARKET, BY OFFERING
7.1 INTRODUCTION
7.2 INTEGRATED SOLUTIONS
7.2.1 RISE IN WORKFORCE CHALLENGES AND COST PRESSURES TO DRIVE ADOPTION
7.3 NICHE/POINT SOLUTIONS
7.3.1 TARGETED AI SOLUTIONS TRANSFORMING PRECISION CARE AND EFFICIENCY IN HEALTHCARE TO BOOST MARKET
7.4 AI TECHNOLOGIES
7.4.1 ABILITY OF CORE AI TECHNOLOGIES TO DRIVE PRECISION, EFFICIENCY, AND INNOVATION TO SUPPORT MARKET GROWTH
7.5 SERVICES
7.5.1 NEED TO EMPOWER NON-CLINICAL HEALTHCARE OPERATIONS TO FUEL MARKET GROWTH
8 AI IN HEALTHCARE MARKET, BY FUNCTION
8.1 INTRODUCTION
8.2 DIAGNOSIS & EARLY DETECTION
8.2.1 PRE-SCREENING
8.2.1.1 Early detection, better outcomes, and cost-effective care associated with pre-screening to boost market
8.2.2 IVD
8.2.2.1 IVD market, by technology
8.2.2.1.1 Immunoassays
8.2.2.1.1.1 Increase in focus on earlier disease detection & personalized treatment planning to drive market
8.2.2.1.2 Clinical chemistry
8.2.2.1.2.1 Increased demand for precision and personalized medicine and efficient healthcare systems to drive market
8.2.2.1.3 Molecular diagnostics
8.2.2.1.3.1 Improved disease detection, personalized treatments, and enhanced outcomes to fuel growth
8.2.2.2 IVD market, by application
8.2.2.2.1 Image analysis & interpretation
8.2.2.2.1.1 Advantages such as enhanced diagnostic accuracy, faster detection, and improved patient outcomes to support growth
8.2.2.2.2 Biomarker discovery & analysis
8.2.2.2.2.1 Ability of AI-based biomarker discovery to enhance disease detection, prognosis, and personalized treatment to drive adoption
