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세계의 헬스케어용 AI 시장 규모, 점유율 및 동향 분석 보고서 : 구성요소별, 용도별, 기술별, 최종 용도별, 지역별, 부문별 예측(2024-2030년)

AI In Healthcare Market Size, Share & Trends Analysis Report By Component (Hardware, Services), By Application, By End-use, By Technology, By Region, And Segment Forecasts, 2024 - 2030
발행일: | 리서치사: Grand View Research | 페이지 정보: 영문 150 Pages | 배송안내 : 2-10일 (영업일 기준)

    
    
    




※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

헬스케어용 AI 시장 성장과 동향 :

Grand View Research, Inc.의 최신 보고서에 따르면, 세계 헬스케어용 AI 시장 규모는 2024-2030년간 38.5%의 연평균 복합 성장률(CAGR)을 나타내고, 2030년까지 1,877억 달러에 달할 것으로 예상됩니다.

AI는 헬스케어 시스템을 변화시키는 힘으로 작용하여 반응형에서 예방적, 예측적, 예방적 모델로의 전환을 가능하게 합니다. 인공지능(AI)이 지원하는 임상 의사결정 지원 시스템은 예측적이고 실시간 분석을 통해 의사 및 의료 전문가에게 힘을 실어주고, 의사결정을 강화하며, 치료의 질을 향상시키고, 궁극적으로 환자 결과를 개선합니다. 또한 AI는 질병 생물학 및 환자 병리에 대한 종합적인 이해를 촉진하여 정밀의료 및 정밀 공중보건 이니셔티브를 발전시킬 수 있습니다.

또한, 빠르게 성장하고 있는 생명과학 R&D 분야에서는 방대한 양의 다차원 데이터를 처리하는 AI의 능력이 중요한 역할을 하는 등 많은 시장 성장 기회를 창출하고 있습니다. 이러한 능력은 새로운 가설의 창출을 가속화하고, 신약 개발 및 재사용 프로세스를 가속화하며, 인실리코(in silico) 기법을 활용하여 비용과 시장 출시 시간을 크게 단축할 수 있습니다. 요컨대, AI는 헬스케어 분야 전반에 걸쳐 혁신과 효율성을 촉진하고 전 세계 의료 서비스 제공에 혁명을 일으키고 있으며, AI 기반 기술은 가상 비서, 로봇 보조 수술, 클레임 관리, 사이버 보안, 환자 관리 등 다양한 헬스케어 분야에 적용되고 있습니다. 다양한 헬스케어 분야에서 구현되고 있습니다.

AI 알고리즘은 환자의 건강 데이터 세트를 사용하여 훈련되어 질병 진단 및 조기 발견을 최적화하고 적시에 치료 요법을 시작할 수 있도록 합니다. 정부 지원책, 자금 조달, 개인 투자자와 벤처캐피털의 투자 증가, AI 전문 스타트업의 출현이 시장 성장을 가속하는 주요 요인으로 작용하고 있습니다. 예를 들어, 2024년 2월, 헬스케어 기업 패브릭은 대화형 AI 기반 헬스케어 플랫폼을 확장하기 위해 6,000만 달러의 시리즈 A 투자를 유치했으며, 2023년 9월, 아마존은 Anthropic과의 제휴를 통해 AI에 40억 달러를 투자할 것이라고 발표했습니다. 를 발표했는데, 이는 거대 하이테크 기업의 헬스케어에 대한 열망을 추진하기 위한 중요한 전략적 움직임입니다.

헬스케어용 AI 시장에서의 스타트업의 부상도 업계 성장의 큰 원동력이 되고 있습니다. 이러한 스타트업의 존재는 투자를 촉진하고, 기술 발전을 촉진하며, 헬스케어용 AI의 적용 범위를 확대합니다. 이러한 스타트업의 노력은 AI 헬스케어 시장의 모멘텀을 가속화하고, 헬스케어 솔루션 제공의 혁신, 효율성, 효과성을 향상시키는 데 기여할 것입니다. 이 분야의 다른 스타트업으로는 액티베이트 헬스(Activate Health), 카훈(Kahun), 라이크마인드(Likeminded), 파마런(Pharmarun) 등이 있습니다.

헬스케어용 AI 시장 보고서 하이라이트

  • 2023년 세계 시장은 소프트웨어 솔루션의 컴포넌트 부문이 46.3%의 가장 큰 매출 점유율로 가장 큰 비중을 차지했습ㄴ니다. 이러한 높은 점유율은 의료 제공업체, 지불자 및 환자들 사이에서 AI 기반 소프트웨어 솔루션이 널리 채택되고 있기 때문으로 분석됩니다.
  • 로봇 보조 수술 용도 부문은 2023년에 가장 큰 매출 점유율로 시장을 장악했고, 2024년에서 2030년까지 가장 빠른 CAGR을 보일 것으로 예상됩니다.
  • 로봇 보조 수술 건수 증가, 새로운 AI 플랫폼 개발의 주요 발전은 로봇 보조 수술에서 AI의 보급을 뒷받침하는 몇 가지 주요 요인입니다.
  • 머신러닝(ML) 기술 부문은 다양한 용도에서 ML 알고리즘의 발전으로 인해 2023년 가장 큰 점유율을 차지했습니다. 이러한 추세는 ML 기술에 대한 수요 증가로 인해 지속될 것으로 예상됩니다.
  • 헬스케어 지불자 최종 용도 부문은 2024-2030년 가장 빠른 CAGR을 보일 것으로 예상됩니다.
  • 2023년에는 북미가 45% 이상의 가장 큰 점유율을 차지하며 업계를 지배했습니다. 이는 헬스케어 IT 인프라의 발전, 첨단 기술 채택 준비, 여러 주요 기업의 존재, 노인 인구 증가, 만성 질환의 유병률 증가에 기인합니다.
  • 아시아태평양에서는 예측 기간 동안 큰 성장이 예상됩니다.

목차

제1장 조사 방법과 범위

제2장 주요 요약

제3장 헬스케어용 AI 시장 변수, 동향, 범위

  • 시장 계통 전망
    • 상위 시장 전망
    • 관련/부수 시장 전망
  • 시장 역학
    • 시장 성장 촉진요인 분석
    • 시장 성장 억제요인 분석
    • 시장 기회 분석
    • 시장이 해결해야 할 과제 분석
  • 사례 연구 : AI를 활용한 헬스케어 실제 도입 성공 사례
  • 헬스케어용 AI 시장 분석 툴
    • 업계 분석 - Porter의 Five Forces 분석
    • PESTEL 분석
    • 업계 분석-COVID-19의 영향

제4장 헬스케어용 AI 시장 : 컴포넌트 추정·동향 분석

  • 정의와 범위
  • 부문 대시보드
  • 헬스케어용 AI 시장 변동 분석
  • 헬스케어용 AI 시장 규모·동향 분석, 컴포넌트별, 2018년-2030년

제5장 헬스케어용 AI 시장 : 용도 추정·동향 분석

  • 정의와 범위
  • 부문 대시보드
  • 헬스케어용 AI 시장 변동 분석
  • 헬스케어용 AI 시장 규모·동향 분석, 용도별, 2018년-2030년

제6장 헬스케어용 AI 시장 : 기술 추정·동향 분석

  • 정의와 범위
  • 부문 대시보드
  • 헬스케어용 AI 시장 변동 분석
  • 헬스케어용 AI 시장 규모·동향 분석, 기술별, 2018년-2030년

제7장 헬스케어용 AI 시장 : 최종 용도 추정·동향 분석

  • 정의와 범위
  • 부문 대시보드
  • 헬스케어용 AI 시장 변동 분석
  • 헬스케어용 AI 시장 규모·동향 분석, 최종 용도별, 2018년-2030년

제8장 헬스케어용 AI 시장 : 지역 추정·동향 분석

  • 지역 시장 대시보드
  • 세계의 지역 시장 현황
  • 시장 규모와 예측·동향 분석, 2018년-2030년
  • 북미
  • 유럽
  • 아시아태평양
  • 라틴아메리카
  • 중동 및 아프리카

제9장 경쟁 구도

  • 주요 시장 진출기업의 최근 동향과 영향 분석
  • 기업/경쟁 분류
  • 벤더 구도
    • Microsoft
    • IBM
    • NVIDIA Corporation
    • Intel Corporation
    • Itrex Group
    • GE Healthcare
    • Medtronic
    • Oracle
    • Medidata
    • Google
    • IQVIA
LSH 24.05.21

AI In Healthcare Market Growth & Trends:

The global AI in healthcare market size is expected to reach USD 187.7 billion by 2030, registering a CAGR of 38.5% from 2024 to 2030, according to a new report by Grand View Research, Inc. AI acts as a transformative force in healthcare systems, shifting them from reactive to proactive, predictive, and preventive models. Clinical decision support systems, fueled by artificial intelligence (AI), empower physicians and healthcare professionals with predictive and real-time analytics, enhancing decision-making and elevating care quality, ultimately resulting in improved patient outcomes. Furthermore, AI facilitates a comprehensive understanding of disease biology and patient pathology, advancing precision medicine and precision public health initiatives.

Furthermore, the growing field of life sciences R&D opens numerous opportunities for market growth, with AI's ability to process vast volumes of multidimensional data playing a crucial role. This capability accelerates the generation of novel hypotheses, expedites drug discovery and repurposing processes, and significantly reduces costs and time to market through the utilization of in silico methods. In essence, AI drives innovation and efficiency across the healthcare sector, revolutionizing healthcare delivery worldwide. AI-based technologies are implemented in various healthcare domains, including virtual assistants, robot-assisted surgeries, claims management, cybersecurity, and patient management.

AI algorithms are trained using patient health datasets to optimize disease diagnosis and early detection, enabling the initiation of timely treatment regimens. Supportive government initiatives, funding, a growing number of investments from private investors and venture capitalists, and the emergence of AI-specialized startups globally are key drivers of market growth. For instance, in February 2024, Fabric, a health tech company, raised USD 60 million in series A funding to expand its conversational AI-powered healthcare platform. In September 2023, Amazon announced a USD 4 billion investment in AI in partnership with Anthropic, representing a significant strategic move toward advancing the tech giant's healthcare aspirations.

The emergence of several startups in the AI healthcare market is another significant driver of industry growth. Their presence stimulates investment, encourages technological advancements, and expands the scope of AI applications in healthcare. The collective efforts of these startups fuel momentum in the AI healthcare market, driving greater innovation, efficiency, and effectiveness in delivering healthcare solutions. Notable startup companies in this space include Activate Health, Kahun, Likeminded, and Pharmarun, among others.

AI In Healthcare Market Report Highlights:

  • The software solutions component segment dominated the global market in 2023 with the largest revenue share of 46.3%. This large share is attributed to the widespread adoption of AI-based software solutions among care providers, payers, and patients
  • The robot-assisted surgery application segment dominated the market in 2023 with the largest revenue share and it is anticipated to witness the fastest CAGR from 2024 to 2030
  • A rise in the volume of robot-assisted surgeries and increased investments in the development of new AI platforms are a few key factors supporting the penetration of AI in robot-assisted surgeries
  • The machine learning (ML) technology segment held the largest share in 2023 as a result of advancements in ML algorithms across various applications. This trend is expected to continue due to the increasing demand for ML technologies
  • The healthcare payers end-use segment is anticipated to experience the fastest CAGR from 2024 to 2030
  • In 2023, North America dominated the industry and held the largest share of over 45% owing to advancements in healthcare IT infrastructure, readiness to adopt advanced technologies, presence of several key players, growing geriatric population, and rising prevalence of chronic diseases
  • In Asia Pacific, the market is anticipated to witness significant growth over the forecast period

Table of Contents

Chapter 1. Methodology and Scope

  • 1.1. Market Segmentation & Scope
  • 1.2. Research Methodology
  • 1.3. Information Procurement
    • 1.3.1. Purchased database
    • 1.3.2. GVR's internal database
    • 1.3.3. Secondary sources
    • 1.3.4. Primary research
    • 1.3.5. Details of primary research
      • 1.3.5.1. Data for primary interviews in North America
      • 1.3.5.2. Data for primary interviews in Europe
      • 1.3.5.3. Data for primary interviews in Asia Pacific
      • 1.3.5.4. Data for primary interviews in Latin America
      • 1.3.5.5. Data for Primary interviews in MEA
  • 1.4. Information or Data Analysis
    • 1.4.1. Data analysis models
  • 1.5. Market Formulation & Data Validation
  • 1.6. Model Details
    • 1.6.1. Commodity flow analysis (Model 1)
    • 1.6.2. Approach 1: Commodity flow approach
    • 1.6.3. Volume price analysis (Model 2)
    • 1.6.4. Approach 2: Volume price analysis
  • 1.7. List of Secondary Sources
  • 1.8. List of Primary Sources
  • 1.9. Objectives

Chapter 2. Executive Summary

  • 2.1. Market Outlook
  • 2.2. Segment Outlook
    • 2.2.1. Component outlook
    • 2.2.2. Application outlook
    • 2.2.3. Technology outlook
    • 2.2.4. End-Use outlook
    • 2.2.5. Regional outlook
  • 2.3. Competitive Insights

Chapter 3. Artificial Intelligence (AI) In Healthcare Market Variables, Trends & Scope

  • 3.1. Market Lineage Outlook
    • 3.1.1. Parent market outlook
    • 3.1.2. Related/ancillary market outlook
  • 3.2. Market Dynamics
    • 3.2.1. Market driver analysis
    • 3.2.2. Market restraint analysis
    • 3.2.3. Market opportunity analysis
    • 3.2.4. Market challenges analysis
  • 3.3. Case Studies: Real-World Implementation Success Stories of AI-Driven Healthcare
  • 3.4. AI In Healthcare Market Analysis Tools
    • 3.4.1. Industry Analysis - Porter's
      • 3.4.1.1. Supplier power
      • 3.4.1.2. Buyer power
      • 3.4.1.3. Substitution threat
      • 3.4.1.4. Threat of new entrant
      • 3.4.1.5. Competitive rivalry
    • 3.4.2. PESTEL Analysis
      • 3.4.2.1. Political landscape
      • 3.4.2.2. Technological landscape
      • 3.4.2.3. Economic landscape
      • 3.4.2.4. Environmental Landscape
      • 3.4.2.5. Legal Landscape
      • 3.4.2.6. Social Landscape
    • 3.4.3. Industry Analysis - COVID-19 impact

Chapter 4. Artificial Intelligence (AI) In Healthcare Market: Component Estimates & Trend Analysis

  • 4.1. Definitions and Scope
  • 4.2. Segment Dashboard
  • 4.3. AI In Healthcare Market Movement Analysis
  • 4.4. AI In Healthcare Market Size & Trend Analysis by Component, 2018 to 2030 (USD Million)
    • 4.4.1. Software Solutions
      • 4.4.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.1.1.1. AI platform
      • 4.4.1.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.1.1.1.2. Application Program Interface (API)
      • 4.4.1.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.1.1.1.3. Machine Learning Framework
      • 4.4.1.1.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.1.1.2. AI Solutions
      • 4.4.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.1.1.2.2. On premise
      • 4.4.1.1.2.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.1.1.2.3. Cloud based
      • 4.4.1.1.2.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 4.4.2. Hardware
      • 4.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.1. Processor
      • 4.4.2.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.1.2. MPU (memory protection unit)
      • 4.4.2.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.1.3. FPGA (Field-programmable gate array)
      • 4.4.2.1.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.1.4. GPU (Graphics processing unit)
      • 4.4.2.1.1.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.1.5. ASIC (Application-specific integrated circuit)
      • 4.4.2.1.1.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.2. Memory
      • 4.4.2.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.3. Network
      • 4.4.2.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.3.2. Adapter
      • 4.4.2.1.3.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.3.3. Interconnect
      • 4.4.2.1.3.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.2.1.3.4. Switch
      • 4.4.2.1.3.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 4.4.3. Services
      • 4.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.3.1.1. Deployment & Integration
      • 4.4.3.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.3.1.2. Support & Maintenance
      • 4.4.3.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 4.4.3.1.3. Others (Consulting, Compliance management etc.)
      • 4.4.3.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 4.4.4. Distributed Denial of Service (DDoS) Mitigation
      • 4.4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 4.4.5. Security Information and Event Management
      • 4.4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 4.4.6. Intrusion Detection System (IDS)/Intrusion Prevention System (IPS)
      • 4.4.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 4.4.7. Others
      • 4.4.7.1. Market estimates and forecast 2018 to 2030 (USD Million)

Chapter 5. Artificial Intelligence (AI) In Healthcare Market: Application Estimates & Trend Analysis

  • 5.1. Definitions and Scope
  • 5.2. Segment Dashboard
  • 5.3. AI In Healthcare Market Movement Analysis
  • 5.4. AI In Healthcare Market Size & Trend Analyses, by Application, 2018 to 2030 (USD Million)
    • 5.4.1. Robot-assisted Surgery
      • 5.4.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.2. Virtual Assistants
      • 5.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.3. Administrative Workflow Assistants
      • 5.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.4. Connected Medical Devices
      • 5.4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.5. Medical Imagining & Diagnosis
      • 5.4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.6. Clinical Trials
      • 5.4.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.7. Fraud Detection
      • 5.4.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.8. Cybersecurity
      • 5.4.8.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.9. Dosage Error Reduction
      • 5.4.9.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.10. Precision Medicine
      • 5.4.10.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.11. Drug Discovery & Development
      • 5.4.11.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.12. Lifestyle Management & Remote Patient Monitoring
      • 5.4.12.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.13. Wearables
      • 5.4.13.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 5.4.14. Others
      • 5.4.14.1. Market estimates and forecast 2018 to 2030 (USD Million)

Chapter 6. Artificial Intelligence (AI) In Healthcare Market: Technology Estimates & Trend Analysis

  • 6.1. Definitions and Scope
  • 6.2. Segment Dashboard
  • 6.3. AI In Healthcare Market Movement Analysis
  • 6.4. AI In Healthcare Market Size & Trend Analyses, by Technology, 2018 to 2030 (USD Million)
    • 6.4.1. Machine Learning
      • 6.4.1.1. Market estimates and forecast 2018 to 2030 (USD million)
      • 6.4.1.1.1. Deep learning
      • 6.4.1.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.1.1.2. Supervised
      • 6.4.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.1.1.3. Unsupervised
      • 6.4.1.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.1.1.4. Others (Reinforcement learning, Semi supervised)
      • 6.4.1.1.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 6.4.2. NLP
      • 6.4.2.1. Market estimates and forecast 2018 to 2030 (USD million)
      • 6.4.2.1.1. Smart Assistance
      • 6.4.2.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.2.1.2. OCR (Optical Character Recognition)
      • 6.4.2.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.2.1.3. Auto Coding
      • 6.4.2.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.2.1.4. Text analytics
      • 6.4.2.1.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.2.1.5. Speech analytics
      • 6.4.2.1.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
      • 6.4.2.1.6. Classification and categorization
      • 6.4.2.1.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 6.4.3. Computer Vision
      • 6.4.3.1. Market estimates and forecast 2018 to 2030 (USD million)
    • 6.4.4. Context-aware Computing
      • 6.4.4.1. Market estimates and forecast 2018 to 2030 (USD million)

Chapter 7. Artificial Intelligence (AI) In Healthcare Market: End-use Estimates & Trend Analysis

  • 7.1. Definitions and Scope
  • 7.2. Segment Dashboard
  • 7.3. AI In Healthcare Market Movement Analysis
  • 7.4. AI In Healthcare Market Size & Trend Analyses, By End-Use, 2018 to 2030 (USD Million)
    • 7.4.1. Healthcare Providers (Hospitals, Outpatient Facilities, and Others)
      • 7.4.1.1. Market estimates and forecast 2018 to 2030 (USD million)
    • 7.4.2. Healthcare Payers
      • 7.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 7.4.3. Healthcare Companies
      • 7.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 7.4.4. Patients
      • 7.4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
    • 7.4.5. Others
      • 7.4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)

Chapter 8. Artificial Intelligence (AI) In Healthcare Market: Regional Estimates & Trend Analysis by Component, Application, Technology & End-use

  • 8.1. Regional Market Dashboard
  • 8.2. Global Regional Market Snapshot
  • 8.3. Market Size, & Forecasts Trend Analysis, 2018 to 2030
  • 8.4. North America
    • 8.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 8.4.2. U.S.
      • 8.4.2.1. U.S. market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.4.3. Canada
      • 8.4.3.1. Canada market estimates and forecast, 2018 - 2030 (USD Million)
  • 8.5. Europe
    • 8.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 8.5.2. UK
      • 8.5.2.1. UK market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.3. Germany
      • 8.5.3.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.4. France
      • 8.5.4.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.5. Italy
      • 8.5.5.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.6. Spain
      • 8.5.6.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.7. Sweden
      • 8.5.7.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.8. Denmark
      • 8.5.8.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.9. Norway
      • 8.5.9.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.5.10. Russia
      • 8.5.10.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
  • 8.6. Asia Pacific
    • 8.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 8.6.2. Japan
      • 8.6.2.1. Japan market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.6.3. China
      • 8.6.3.1. China market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.6.4. India
      • 8.6.4.1. China market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.6.5. Singapore
      • 8.6.5.1. China market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.6.6. Australia
      • 8.6.6.1. China market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.6.7. South Korea
      • 8.6.7.1. China market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.6.8. Thailand
      • 8.6.8.1. China market estimates and forecast, 2018 - 2030 (USD Million)
  • 8.7. Latin America
    • 8.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 8.7.2. Brazil
      • 8.7.2.2. Brazil market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.7.3. Mexico
      • 8.7.3.2. Mexico market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.7.4. Argentina
      • 8.7.4.1. China market estimates and forecast, 2018 - 2030 (USD Million)
  • 8.8. MEA
    • 8.8.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 8.8.2. South Africa
      • 8.8.2.1. South Africa market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.8.3. Saudi Arabia
      • 8.8.3.1. Saudi Arabia market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.8.4. UAE
      • 8.8.4.1. China market estimates and forecast, 2018 - 2030 (USD Million)
    • 8.8.5. Kuwait
      • 8.8.5.1. China market estimates and forecast, 2018 - 2030 (USD Million)

Chapter 9. Competitive Landscape

  • 9.1. Recent Developments & Impact Analysis, By Key Market Participants
  • 9.2. Company/Competition Categorization
    • 9.2.1. Key Innovators
    • 9.2.2. Market Leaders
    • 9.2.3. Emerging Players
  • 9.3. Vendor Landscape
    • 9.3.1. Key company market share analysis, 2023
    • 9.3.2. Microsoft
      • 9.3.2.1. Company overview
      • 9.3.2.2. Financial performance
      • 9.3.2.3. Product benchmarking
      • 9.3.2.4. Strategic initiatives
    • 9.3.3. IBM
      • 9.3.3.1. Company overview
      • 9.3.3.2. Financial performance
      • 9.3.3.3. Product benchmarking
      • 9.3.3.4. Strategic initiatives
    • 9.3.4. NVIDIA Corporation
      • 9.3.4.1. Company overview
      • 9.3.4.2. Financial performance
      • 9.3.4.3. Product benchmarking
      • 9.3.4.4. Strategic initiatives
    • 9.3.5. Intel Corporation
      • 9.3.5.1. Company overview
      • 9.3.5.2. Financial performance
      • 9.3.5.3. Product benchmarking
      • 9.3.5.4. Strategic initiatives
    • 9.3.6. Itrex Group
      • 9.3.6.1. Company overview
      • 9.3.6.2. Financial performance
      • 9.3.6.3. Product benchmarking
      • 9.3.6.4. Strategic initiatives
    • 9.3.7. GE Healthcare
      • 9.3.7.1. Company overview
      • 9.3.7.2. Financial performance
      • 9.3.7.3. Product benchmarking
      • 9.3.7.4. Strategic initiatives
    • 9.3.8. Medtronic
      • 9.3.8.1. Company overview
      • 9.3.8.2. Financial performance
      • 9.3.8.3. Product benchmarking
      • 9.3.8.4. Strategic initiatives
    • 9.3.9. Oracle
      • 9.3.9.1. Company overview
      • 9.3.9.2. Financial performance
      • 9.3.9.3. Product benchmarking
      • 9.3.9.4. Strategic initiatives
    • 9.3.10. Medidata
      • 9.3.10.1. Company overview
      • 9.3.10.2. Financial performance
      • 9.3.10.3. Product benchmarking
      • 9.3.10.4. Strategic initiatives
    • 9.3.11. Google
      • 9.3.11.1. Company overview
      • 9.3.11.2. Financial performance
      • 9.3.11.3. Product benchmarking
      • 9.3.11.4. Strategic initiatives
    • 9.3.12. IQVIA
      • 9.3.12.1. Company overview
      • 9.3.12.2. Financial performance
      • 9.3.12.3. Product benchmarking
      • 9.3.12.4. Strategic initiatives
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