시장보고서
상품코드
1297159

세계의 의료용 AI 시장 평가 : 구성요소별, 기술별, 용도별, 최종사용자별, 지역별

Artificial Intelligence in Healthcare Market Assessment, By Component, By Technology, By Application, By End-user, By Region

발행일: | 리서치사: Market Xcel - Markets and Data | 페이지 정보: 영문 124 Pages | 배송안내 : 3-5일 (영업일 기준)


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

세계 의료용 AI 시장 규모는 2022년 164억 7,000만 달러에서 2030년 1,983억 2,000만 달러에 달하고, 2023-2030년의 예측 기간 동안 36.48%의 CAGR을 나타낼 것으로 예상됩니다. 데이터 생성, 개인화된 의료 및 정밀의료에 대한 수요 증가, 의료 영상 및 진단에 대한 AI 적용 확대, 고령자를 위한 AI 기반 도구의 잠재력 증가 등의 요인이 시장을 주도하고 있습니다.

이 보고서는 세계 의료용 AI 시장에 대해 조사 분석했으며, 시장 규모와 예측, 시장 역학, 주요 기업 현황과 전망 등의 정보를 제공합니다.

목차

제1장 조사 방법

제2장 프로젝트의 범위와 정의

제3장 의료용 AI 시장에 대한 COVID-19의 영향

제4장 러시아·우크라이나 전쟁의 영향

제5장 주요 요약

제6장 세계의 의료용 AI 시장 전망(2016년-2030년)

  • 시장 규모와 예측
    • 금액
  • 컴포넌트별
    • 하드웨어
    • 소프트웨어
    • 서비스
  • 기술별
    • 머신러닝
    • 자연언어처리
    • 상황인식 컴퓨팅
    • 컴퓨터 비전
    • 로봇 프로세스 자동화(RPA)
    • 기타
  • 용도별
    • 로봇 보조 수술
    • 관리 워크플로우 지원
    • 사이버 보안
    • 가상 간호 보조
    • 임상시험
    • 진단
    • 고객 서비스 챗봇
    • Drug Discovery
    • 기타
  • 최종사용자별
    • 병원 및 진료소
    • 제약 및 바이오테크놀러지
    • 환자
    • 기타
  • 지역별
    • 북미
    • 유럽
    • 아시아태평양
    • 중동 및 아프리카
    • 남미
  • 시장 점유율 : 기업별(2022년)

제7장 세계의 의료용 AI 시장 전망 : 지역별(2016년-2030년)

  • 북미
    • 컴포넌트별
    • 기술별
    • 용도별
    • 최종사용자별
  • 미국
    • 컴포넌트별
    • 기술별
    • 용도별
    • 최종사용자별
  • 캐나다
  • 멕시코
  • 유럽
    • 독일
    • 프랑스
    • 이탈리아
    • 영국
    • 러시아
    • 네덜란드
    • 스페인
    • 터키
    • 폴란드
  • 남미
    • 브라질
    • 아르헨티나
  • 아시아태평양
    • 인도
    • 중국
    • 일본
    • 호주
    • 베트남
    • 한국
    • 인도네시아
    • 필리핀
  • 중동 및 아프리카
    • 사우디아라비아
    • 아랍에미리트(UAE)
    • 남아프리카공화국

제8장 시장 매핑(2022년)

  • 컴포넌트별
  • 기술별
  • 용도별
  • 최종사용자별
  • 지역별

제9장 거시환경과 업계 구조

  • 수급 분석
  • 수출입 분석
  • 밸류체인 분석
  • PESTEL 분석
  • Porter의 Five Forces 분석

제10장 시장 역학

  • 성장 촉진요인
  • 성장 억제요인(과제, 성장 억제요인)

제11장 주요 기업 상황

  • 시장 리더 주요 5개사의 경쟁 매트릭스
  • 시장 리더 주요 5개사의 시장 매출 분석(2022년)
  • 인수합병(M&A)/합작투자(해당하는 경우)
  • SWOT 분석(시장 진출기업 5개사)
  • 특허 분석(해당하는 경우)

제12장 가격 분석

제13장 사례 연구

제14장 주요 기업 전망

  • Nvidia Corporation
  • Intel Corporation
  • Koninklijke Philips N.V
  • Microsoft Corporation
  • Google LLC
  • Siemens Healthineers GmbH
  • Medtronic PLC
  • Amazon Web Services, Inc.
  • CloudMex Inc.
  • IBM Corporation
  • Babylon Health Services Ltd
  • Komodo Health, Inc.
  • 기타

제15장 전략적 추천 사항

제16장 당사에 대해/면책사항

LSH 23.07.04

The Global Artificial Intelligence (AI) in Healthcare Market size was valued at USD 16.47 billion in 2022 which is expected to reach USD 198.32 billion in 2030 growing at a CAGR of 36.48% for the forecasted period between 2023 and 2030. The market is being driven by factors such as increasing adoption of AI technologies, generation of large volumes of patient-health-related data, increasing demand for personalized and precision medicine, growing application of AI in medical imaging and diagnostics, and increasing potential for AI-based tools for the elderly population. Recent advancements in AI have been accelerated by the impact of COVID-19, thus making AI an indispensable part of healthcare.

As AI technologies became increasingly popular in healthcare applications, key market players focused on product innovation and technical partnerships to extend their product range and meet increasing demand. For instance, in 2022, Amazon Web Services launched Amazon Omics for precision medicine. Amazon Omics uses AI, ML, and deep learning-based algorithms to aid healthcare professionals in gaining better understanding during patient care. This service is designed to aid in identifying the most effective treatment or prevention choices by efficiently managing complex bioinformatics tasks.

Growing Application in Medical Imaging and Diagnostics

Researchers are increasingly exploring new methods to incorporate artificial intelligence into medical imaging. In recent times, research institutions and universities have been actively working towards expanding the use of AI in cancer treatment. The COVID-19 pandemic led to delays in diagnosing and screening of diseases, including routine check-ups and cancer screenings, which had resulted in the detection of more advanced stages of cancer. Deep learning algorithms have emerged as the preferred approach for analyzing radiology imaging, such as CT, MRI, PET, ultrasound, and addressing diverse tasks like tumor detection, segmentation, and disease detection. Multiple studies have demonstrated significant performance enhancements of deep learning-based models compared to conventional machine learning algorithms.

Adoption of Machine Learning in Healthcare

In the past five years, significant progress has been made in AI, ML and data science, leading to numerous technological advancements. The convergence of fast computer processing, expansive data repositories, and a robust pool of AI experts has facilitated swift growth in AI tools and technology in the healthcare sector. As a result, there is a huge demand where AI technology is poised to revolutionize society through its widespread adoption and profound impact. In the healthcare sector, AI is being widely used in dermatology, electronic health records (EHR), surgical robotics, drug manufacturing, psychiatry etc. AI dermatologist, an innovative prediagnostic app, is able to identify one of the most dangerous diseases which is skin cancer. Globally, more than 2 people die of this disease every hour.

Government Initiatives & Regulations

In June 2023, the U.S government announced its initiatives to ensure the safe progress and implementation of artificial intelligence. Additionally, they are inviting the public to actively contribute to the formulation of the government's AI strategies. Healthcare experts have been raising awareness about the necessity for the healthcare industry to adopt a proactive approach regarding AI safety. They emphasize the importance of developing and implementing measures to ensure the transparent deployment of AI in clinical settings. For instance, on 27th October 2021, the Food and Drug Administration (FDA) provided specific guidance regarding the use of AI in medical devices. The FDA, in collaboration with Health Canada and the United Kingdom's Medicines and Healthcare products Regulatory Agency, published guiding principles that outline the appropriate utilization of AI and machine learning (ML) in medical devices.

North America to Dominate

In 2022, AI in healthcare market was largely dominated by North America region This is primarily due to the growing utilization of AI/ML technologies, advancements in healthcare IT infrastructure, initiatives taken by the government, and the presence of numerous tech giants. The United States has witnessed large investments in AI/ML, which has resulted in the substantial influence of these technologies. The country stands out as the primary destination for many investment deals in AI startups.

The level of funding in the United States experienced significant growth in 2020 and 2021. For instance, Insitro, a company focused on utilizing machine learning for drug discovery and development, secured USD 400 million in Series C financing in March 2021. Canada Pension Plan Investment Board (CPP Investments) lead the financing round, accompanied by notable contributions from existing investors such as Andreessen Horowitz, funds and accounts advised by T. Rowe Price Associates, Inc., Casdin Capital, and funds and accounts managed by BlackRock.

The United States holds the top position globally in terms of preparedness for integrating AI in the public sector, with an average score of 85.48 out of 100. The country excels in crucial areas such as AI vision, as well as AI governance and ethics.

Robot-Assisted-Surgery Contributes Largely to Market Share

The robot-assisted-surgery segment dominated the market in 2022 and accounted for the largest market share during the forecasted period. Robotic surgery has witnessed a relatively recent integration of AI, primarily in imaging and navigation applications. Initially, the emphasis was on detecting features and assisting surgeons through computer-guided interventions for pre-operative planning and intra-operative guidance. This gradual transformation in surgical practice can be attributed to technological advancements in imaging, navigation, and robotic interventions facilitated by AI. Incorporating AI in surgical robotics has several advantages such as AI's ability to learn from large data sets, identifying new trends and reducing physical stress of the surgeon. For instance, the da Vinci Surgical System, equipped with AI capabilities, allows surgeons to perform precise and minimally invasive prostatectomies. AI algorithms assist in preoperative planning, identifying the optimal approach and assisting surgeons in navigating complex anatomical structures during the procedure.

Impact of COVID-19

The COVID-19 pandemic expedited the acceptance of artificial intelligence in the healthcare sector. AI-powered solutions and tools have the capability to operate swiftly, can be implemented on a large scale, and can adapt to the rapidly changing technological environment. Various market players, including startups, established corporations, universities, and others, are actively contributing their skills and offerings in the field of AI. For instance, companies like Current Health , a remote-monitoring startup based in the U.K., helped prominent institutions such as Mayo Clinic and Baptist Health during COVID-19. Such startups play a crucial role in the industry's swift adoption of digital solutions and are rapidly expanding their operations to meet the increasing demand. Major tech companies such as Microsoft, Google, Apple, Amazon, and Facebook are engaged in various initiatives pertaining to remote communication between patients and healthcare providers, contact tracing, drug development, and many more features.

Impact of Russia-Ukraine War

The war between Russia and Ukraine led to closure of business operations by many tech and healthcare organizations. Organizations such as Siemens Healthcare GmbH, IBM Corporation, Nvidia Corporation, Microsoft Corporation and many others shutdown their offices and business activities in Russia. Sanctions were imposed by more than 30 countries including Australia, Canada, Norway, Japan, United States, among others. Siemens AG exited the Russian market due to the Russia-Ukraine war. The company initiated the process to terminate its industrial operations and ceased all industrial business activities including healthcare in May 2022.

Key Player Landscape and Outlook

The global AI in healthcare market is highly competitive, with several established players and new entrants competing for market share. Some of the trends taking place in the market are advancements in natural language processing & conversational AI, and integration of electronic health records (EHRs) & wearables. Businesses are placing their emphasis on automating repetitive tasks, enhancing customer service through chatbots, optimizing supply chain management, and employing predictive analytics to make more informed decisions, all in pursuit of gaining a competitive edge in the market.

For instance, in 2023, Epic Systems Corporation announced its partnership with Microsoft Corporation, for a primary objective of integrating the Azure OpenAI service into Epic's electronic health record (EHR) software. The collaboration aims to enhance the efficiency of both physicians and back-office professionals. Initially, Epic's focus lies in utilizing OpenAI's GPT-4 AI language model to assist healthcare workers in drafting message responses to patients and to analyze medical records for identifying trends.

Table of Contents

1. Research Methodology

2. Project Scope & Definitions

3. Impact of COVID-19 on Artificial Intelligence in Healthcare Market

4. Impact of Russia-Ukraine War

5. Executive Summary

6. Global Artificial Intelligence in Healthcare Market Outlook, 2016-2030F

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. By Component
    • 6.2.1. Hardware
      • 6.2.1.1. Processor
      • 6.2.1.2. Memory Units
      • 6.2.1.3. Network
      • 6.2.1.4. Others
    • 6.2.2. Software
      • 6.2.2.1. Platform
      • 6.2.2.2. Solution
    • 6.2.3. Services
      • 6.2.3.1. Deployment & Integration
      • 6.2.3.2. Support & Maintenance
  • 6.3. By Technology
    • 6.3.1. Machine Learning
      • 6.3.1.1. Deep Learning
      • 6.3.1.2. Supervised Learning
      • 6.3.1.3. Unsupervised Learning
      • 6.3.1.4. Reinforcement Learning
      • 6.3.1.5. Others
    • 6.3.2. Natural Language Processing
    • 6.3.3. Context-Aware Computing
    • 6.3.4. Computer Vision
    • 6.3.5. Robotic Process Automation (RPA)
    • 6.3.6. Others
  • 6.4. By Application
    • 6.4.1. Robot-Assisted Surgery
    • 6.4.2. Administrative Workflow Assistance
    • 6.4.3. Cybersecurity
    • 6.4.4. Virtual Nursing Assistant
    • 6.4.5. Clinical Trials
    • 6.4.6. Diagnosis
    • 6.4.7. Customer Service Chatbots
    • 6.4.8. Drug Discovery
    • 6.4.9. Others
  • 6.5. By End-user
    • 6.5.1. Hospitals & Clinics
    • 6.5.2. Pharmaceutical & Biotechnology
    • 6.5.3. Patients
    • 6.5.4. Others
  • 6.6. By Region
    • 6.6.1. North America
    • 6.6.2. Europe
    • 6.6.3. Asia-Pacific
    • 6.6.4. Middle East and Africa
    • 6.6.5. South America
  • 6.7. By Company Market Share (%), 2022

7. Global Artificial Intelligence in Healthcare Market Outlook, By Region, 2016-2030F

  • 7.1. North America*
    • 7.1.1. By Component
      • 7.1.1.1. Hardware
      • 7.1.1.1.1. Processor
      • 7.1.1.1.2. Memory Units
      • 7.1.1.1.3. Network
      • 7.1.1.1.4. Others
      • 7.1.1.2. Software
      • 7.1.1.2.1. Platform
      • 7.1.1.2.2. Solution
      • 7.1.1.3. Services
      • 7.1.1.3.1. Deployment & Integration
      • 7.1.1.3.2. Support & Maintenance
    • 7.1.2. By Technology
      • 7.1.2.1. Machine Learning
      • 7.1.2.1.1. Deep Learning
      • 7.1.2.1.2. Supervised Learning
      • 7.1.2.1.3. Unsupervised Learning
      • 7.1.2.1.4. Reinforcement Learning
      • 7.1.2.1.5. Others
      • 7.1.2.2. Natural Language Processing
      • 7.1.2.3. Context-Aware Computing
      • 7.1.2.4. Computer Vision
      • 7.1.2.5. Robotic Process Automation (RPA)
      • 7.1.2.6. Others
    • 7.1.3. By Application
      • 7.1.3.1. Robot-Assisted Surgery
      • 7.1.3.2. Administrative Workflow Assistance
      • 7.1.3.3. Cybersecurity
      • 7.1.3.4. Virtual Nursing Assistant
      • 7.1.3.5. Clinical Trials
      • 7.1.3.6. Diagnosis
      • 7.1.3.7. Customer Service Chatbots
      • 7.1.3.8. Drug Discovery
      • 7.1.3.9. Others
    • 7.1.4. By End-user
      • 7.1.4.1. Hospitals & Clinics
      • 7.1.4.2. Pharmaceutical & Biotechnology
      • 7.1.4.3. Patients
      • 7.1.4.4. Others
  • 7.2. United States*
    • 7.2.1. By Component
      • 7.2.1.1. Hardware
      • 7.2.1.1.1. Processor
      • 7.2.1.1.2. Memory Units
      • 7.2.1.1.3. Network
      • 7.2.1.1.4. Others
      • 7.2.1.2. Software
      • 7.2.1.2.1. Platform
      • 7.2.1.2.2. Solution
      • 7.2.1.3. Services
      • 7.2.1.3.1. Deployment & Integration
      • 7.2.1.3.2. Support & Maintenance
    • 7.2.2. By Technology
      • 7.2.2.1. Machine Learning
      • 7.2.2.1.1. Deep Learning
      • 7.2.2.1.2. Supervised Learning
      • 7.2.2.1.3. Unsupervised Learning
      • 7.2.2.1.4. Reinforcement Learning
      • 7.2.2.1.5. Others
      • 7.2.2.2. Natural Language Processing
      • 7.2.2.3. Context-Aware Computing
      • 7.2.2.4. Computer Vision
      • 7.2.2.5. Robotic Process Automation (RPA)
      • 7.2.2.6. Others
    • 7.2.3. By Application
      • 7.2.3.1. Robot-Assisted Surgery
      • 7.2.3.2. Administrative Workflow Assistance
      • 7.2.3.3. Cybersecurity
      • 7.2.3.4. Virtual Nursing Assistant
      • 7.2.3.5. Clinical Trials
      • 7.2.3.6. Diagnosis
      • 7.2.3.7. Customer Service Chatbots
      • 7.2.3.8. Drug Discovery
      • 7.2.3.9. Others
    • 7.2.4. By End-user
      • 7.2.4.1. Hospitals & Clinics
      • 7.2.4.2. Pharmaceutical & Biotechnology
      • 7.2.4.3. Patients
      • 7.2.4.4. Others
  • 7.3. Canada
  • 7.4. Mexico

All segments will be provided for all regions and countries covered

  • 7.5. Europe
    • 7.5.1. Germany
    • 7.5.2. France
    • 7.5.3. Italy
    • 7.5.4. United Kingdom
    • 7.5.5. Russia
    • 7.5.6. Netherlands
    • 7.5.7. Spain
    • 7.5.8. Turkey
    • 7.5.9. Poland
  • 7.6. South America
    • 7.6.1. Brazil
    • 7.6.2. Argentina
  • 7.7. Asia-Pacific
    • 7.7.1. India
    • 7.7.2. China
    • 7.7.3. Japan
    • 7.7.4. Australia
    • 7.7.5. Vietnam
    • 7.7.6. South Korea
    • 7.7.7. Indonesia
    • 7.7.8. Philippines
  • 7.8. Middle East & Africa
    • 7.8.1. Saudi Arabia
    • 7.8.2. UAE
    • 7.8.3. South Africa

8. Market Mapping, 2022

  • 8.1. By Component
  • 8.2. By Technology
  • 8.3. By Application
  • 8.4. By End-user
  • 8.5. By Region

9. Macro Environment and Industry Structure

  • 9.1. Supply Demand Analysis
  • 9.2. Import Export Analysis
  • 9.3. Value Chain Analysis
  • 9.4. PESTEL Analysis
    • 9.4.1. Political Factors
    • 9.4.2. Economic System
    • 9.4.3. Social Implications
    • 9.4.4. Technological Advancements
    • 9.4.5. Environmental Impacts
    • 9.4.6. Legal Compliances and Regulatory Policies (Statutory Bodies Included)
  • 9.5. Porter's Five Forces Analysis
    • 9.5.1. Supplier Power
    • 9.5.2. Buyer Power
    • 9.5.3. Substitution Threat
    • 9.5.4. Threat from New Entrant
    • 9.5.5. Competitive Rivalry

10. Market Dynamics

  • 10.1. Growth Drivers
  • 10.2. Growth Inhibitors (Challenges and Restraints)

11. Key Players Landscape

  • 11.1. Competition Matrix of Top Five Market Leaders
  • 11.2. Market Revenue Analysis of Top Five Market Leaders (in %, 2022)
  • 11.3. Mergers and Acquisitions/Joint Ventures (If Applicable)
  • 11.4. SWOT Analysis (For Five Market Players)
  • 11.5. Patent Analysis (If Applicable)

12. Pricing Analysis

13. Case Studies

14. Key Players Outlook

  • 14.1. Nvidia Corporation
    • 14.1.1. Company Details
    • 14.1.2. Key Management Personnel
    • 14.1.3. Products & Services
    • 14.1.4. Financials (As reported)
    • 14.1.5. Key Market Focus & Geographical Presence
    • 14.1.6. Recent Developments
  • 14.2. Intel Corporation
  • 14.3. Koninklijke Philips N.V
  • 14.4. Microsoft Corporation
  • 14.5. Google LLC
  • 14.6. Siemens Healthineers GmbH
  • 14.7. Medtronic PLC
  • 14.8. Amazon Web Services, Inc.
  • 14.9. CloudMex Inc.
  • 14.10. IBM Corporation
  • 14.11. Babylon Health Services Ltd
  • 14.12. Komodo Health, Inc.
  • 14.13. Others

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work

15. Strategic Recommendations

16. About Us & Disclaimer

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