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市場調査レポート

医療向け人工知能 (AI) の世界市場 - 2025年までの予測:マシンラーニング (ML)、自然言語処理 (NLP)、状況認識コンピューティング、コンピュータービジョン

Artificial Intelligence in Healthcare Market by Offering (Hardware, Software, Services), Technology (Machine Learning, NLP, Context-Aware Computing, Computer Vision), End-Use Application, End User, and Geography - Global Forecast to 2025

発行 MarketsandMarkets 商品コード 500057
出版日 ページ情報 英文 217 Pages
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医療向け人工知能 (AI) の世界市場 - 2025年までの予測:マシンラーニング (ML)、自然言語処理 (NLP)、状況認識コンピューティング、コンピュータービジョン Artificial Intelligence in Healthcare Market by Offering (Hardware, Software, Services), Technology (Machine Learning, NLP, Context-Aware Computing, Computer Vision), End-Use Application, End User, and Geography - Global Forecast to 2025
出版日: 2018年12月17日 ページ情報: 英文 217 Pages
概要

医療向け人工知能 (AI) 市場は、2018年の21億米ドルから、2025年までに361億米ドルまで拡大すると見られています。市場は、2018年〜2025年のCAGR (複合年間成長率) で、50.2%の成長が予測されています。

当レポートでは、世界の医療向け人工知能 (AI) 市場について調査分析し、市場概要、産業動向、セグメント別の市場分析、競合情勢、主要企業などについて、体系的な情報を提供しています。

FIGURE 12 AI IN HEALTHCARE MARKET

第1章 イントロダクション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 重要考察

  • 医療向け人工知能 (AI) 市場の魅力的な機会
  • 医療向け人工知能 (AI) 市場:提供別
  • 医療向け人工知能 (AI) 市場:技術別
  • 欧州 - 医療向け人工知能 (AI) 市場:エンドユーザー別、国別
  • 医療向け人工知能 (AI) 市場:国別

第5章 市場概要

  • イントロダクション
  • 市場力学
    • 促進要因
    • 抑制要因
    • 機会
    • 課題
  • バリューチェーン分析
  • ケーススタディ

第6章 医療向け人工知能 (AI) の世界市場:提供別

  • イントロダクション
  • ハードウェア
  • ソフトウェア
  • サービス

第7章 医療向け人工知能 (AI) の世界市場:技術別

  • イントロダクション
  • マシンラーニング (ML)
  • 自然言語処理 (NLP)
  • 状況認識コンピューティング
  • コンピュータービジョン

第8章 医療向け人工知能 (AI) の世界市場:最終用途別

  • イントロダクション
  • 患者データ・リスク解析
  • 入院患者治療・病院管理
  • 医用画像診断
  • ライフスタイル管理・モニタリング
  • 仮想アシスタント
  • 創薬
  • 研究
  • 医療支援ロボット
  • 精密医療
  • 救急医療室・手術
  • ウェアラブル
  • メンタルヘルス

第9章 医療向け人工知能 (AI) の世界市場:エンドユーザー別

  • イントロダクション
  • 病院・医療提供者
  • 患者
  • 製薬・バイオテクノロジー企業
  • 保険者
  • その他

第10章 医療向け人工知能 (AI) の世界市場:地域別

  • イントロダクション
  • 北米
  • 欧州
  • アジア太平洋地域
  • その他

第11章 競合情勢

  • 概要
  • 企業のランキング
  • 競合シナリオ

第12章 企業プロファイル

  • 主要企業
    • NVIDIA
    • INTEL
    • IBM
    • GOOGLE
    • MICROSOFT
    • GENERAL ELECTRIC (GE) COMPANY
    • SIEMENS HEALTHINEERS
    • MEDTRONIC
    • MICRON TECHNOLOGY
    • AMAZON WEB SERVICES (AWS)
  • その他の主要企業
    • JOHNSON & JOHNSON SERVICES
    • KONINKLIJKE PHILIPS
    • GENERAL VISION
  • 企業プロファイル:用途別
    • 患者データ・リスク解析
      • CLOUDMEDX
      • ONCORA MEDICAL
      • ZEPHYR HEALTH
      • SENTRIAN
      • CARESKORE
      • LINGUAMATICS
    • 医用画像診断
      • ENLITIC
      • BAY LABS
      • BUTTERFLY NETWORKS
      • IMAGIA CYBERNETICS
    • 精密医療
      • PRECISION HEALTH AI
      • COTA
      • FDNA
    • 創薬
      • RECURSION PHARMACEUTICALS
      • ATOMWISE
      • DEEP GENOMICS
      • CLOUD PHARMACEUTICALS
    • ライフスタイル管理・モニタリング
      • WELLTOK
      • VITAGENE
      • LUCINA HEALTH
    • 仮想アシスタント
      • NEXT IT
      • BABYLON
      • MDLIVE
    • ウェアラブル
      • MAGNEA
      • PHYSIQ
      • CYRCADIA HEALTH
    • 救急医療室・手術
      • CARESYNTAX
      • GAUSS SURGICAL
      • PERCEIVE3D
      • MAXQ AI
    • 入院患者治療・病院管理
      • QVENTUS
      • WORKFUSION
    • 研究
      • ICARBONX
      • DESKTOP GENETICS
    • メンタルヘルス
      • GINGER.IO
      • X2AI
      • BIOBEATS
    • 医療支援ロボット
      • PILLO
      • CATALIA HEALTH

第13章 付録

図表

LIST OF TABLES

  • TABLE 1: INCREASE IN NEUROIMAGING AND GENETICS DATA, AND COMPLEXITY RELATIVE TO COMPUTATIONAL POWER
  • TABLE 2: PRICE COMPARISON: AI CHIPSETS (LEADING COMPANIES)
  • TABLE 3: AI IN HEALTHCARE MARKET, BY OFFERING, 2015-2025 (USD MILLION)
  • TABLE 4: AI IN HEALTHCARE MARKET, BY HARDWARE, 2015-2025 (USD MILLION)
  • TABLE 5: AI IN HEALTHCARE MARKET FOR HARDWARE, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 6: AI IN HEALTHCARE MARKET, BY PROCESSOR, 2015-2025 (USD MILLION)
  • TABLE 7: AI IN HEALTHCARE MARKET FOR OFFERING, BY SOFTWARE, 2015-2025 (USD MILLION)
  • TABLE 8: AI IN HEALTHCARE MARKET FOR SOFTWARE, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 9: AI IN HEALTHCARE MARKET FOR SOLUTION, BY DEPLOYMENT, 2015-2025 (USD MILLION)
  • TABLE 10: AI IN HEALTHCARE MARKET FOR SOFTWARE, BY PLATFORM, 2015-2025 (USD MILLION)
  • TABLE 11: AI IN HEALTHCARE MARKET, BY SERVICES, 2015-2025 (USD MILLION)
  • TABLE 12: AI IN HEALTHCARE MARKET FOR SERVICES, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 13: AI IN HEALTHCARE MARKET, BY TECHNOLOGY, 2015-2025 (USD MILLION)
  • TABLE 14: AI IN HEALTHCARE MARKET FOR MACHINE LEARNING, BY TYPE, 2015-2025 (USD MILLION)
  • TABLE 15: AI IN HEALTHCARE MARKET FOR NATURAL LANGUAGE PROCESSING, BY TYPE, 2015-2025 (USD MILLION)
  • TABLE 16: AI IN HEALTHCARE MARKET FOR CONTEXT-AWARE COMPUTING, BY TYPE, 2015-2025 (USD MILLION)
  • TABLE 17: AI IN HEALTHCARE MARKET, BY END-USE APPLICATION, 2015-2025 (USD MILLION)
  • TABLE 18: AI IN HEALTHCARE MARKET FOR PATIENT DATA AND RISK ANALYSIS, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 19: AI IN HEALTHCARE MARKET FOR PATIENT DATA AND RISK ANALYSIS, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 20: AI IN HEALTHCARE MARKET FOR IN-PATIENT CARE & HOSPITAL MANAGEMENT, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 21: AI IN HEALTHCARE MARKET FOR IN-PATIENT CARE AND HOSPITAL MANAGEMENT, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 22: AI IN HEALTHCARE MARKET FOR MEDICAL IMAGING AND DIAGNOSTICS, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 23: AI IN HEALTHCARE MARKET FOR MEDICAL IMAGING AND DIAGNOSTICS, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 24: AI IN HEALTHCARE MARKET FOR LIFESTYLE MANAGEMENT & MONITORING, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 25: AI IN HEALTHCARE MARKET FOR LIFESTYLE MANAGEMENT & MONITORING, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 26: AI IN HEALTHCARE MARKET FOR VIRTUAL ASSISTANT, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 27: AI IN HEALTHCARE MARKET FOR VIRTUAL ASSISTANT, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 28: AI IN HEALTHCARE MARKET FOR DRUG DISCOVERY, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 29: AI IN HEALTHCARE MARKET FOR DRUG DISCOVERY, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 30: AI IN HEALTHCARE MARKET FOR RESEARCH, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 31: AI IN HEALTHCARE MARKET FOR RESEARCH, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 32: AI IN HEALTHCARE MARKET FOR HEALTHCARE ASSISTANCE ROBOTS, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 33: AI IN HEALTHCARE MARKET FOR HEALTHCARE ASSISTANCE ROBOTS, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 34: AI IN HEALTHCARE MARKET FOR PRECISION MEDICINE, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 35: AI IN HEALTHCARE MARKET FOR PRECISION MEDICINE, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 36: AI IN HEALTHCARE MARKET FOR EMERGENCY ROOM & SURGERY, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 37: AI IN HEALTHCARE MARKET FOR EMERGENCY ROOM & MONITORING, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 38: AI IN HEALTHCARE MARKET FOR WEARABLES, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 39: AI IN HEALTHCARE MARKET FOR WEARABLES, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 40: AI IN HEALTHCARE MARKET FOR MENTAL HEALTH, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 41: AI IN HEALTHCARE MARKET FOR MENTAL HEALTH, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 42: AI IN HEALTHCARE MARKET, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 43: AI IN HEALTHCARE MARKET FOR HOSPITALS AND PROVIDERS, BY APPLICATION, 2015-2025 (USD MILLION)
  • TABLE 44: AI IN HEALTHCARE MARKET FOR HOSPITALS AND PROVIDERS, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 45: AI IN HEALTHCARE MARKET FOR PATIENTS, BY APPLICATION, 2015-2025 (USD MILLION)
  • TABLE 46: AI IN HEALTHCARE MARKET FOR PATIENTS, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 47: AI IN HEALTHCARE MARKET FOR PHARMACEUTICAL AND BIOTECHNOLOGY COMPANIES, BY APPLICATION, 2015-2025 (USD MILLION)
  • TABLE 48: AI IN HEALTHCARE MARKET FOR PHARMACEUTICAL AND BIOTECHNOLOGY COMPANIES, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 49: AI IN HEALTHCARE MARKET FOR HEALTHCARE PAYERS, BY APPLICATION, 2015-2025 (USD MILLION)
  • TABLE 50: AI IN HEALTHCARE MARKET FOR HEALTHCARE PAYERS, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 51: AI IN HEALTHCARE MARKET FOR OTHERS, BY APPLICATION, 2015-2025 (USD MILLION)
  • TABLE 52: AI IN HEALTHCARE MARKET FOR OTHERS, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 53: AI IN HEALTHCARE MARKET, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 54: AI IN HEALTHCARE MARKET IN NORTH AMERICA, BY COUNTRY, 2015-2025(USD MILLION)
  • TABLE 55: AI IN HEALTHCARE MARKET IN NORTH AMERICA, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 56: AI IN HEALTHCARE MARKET IN NORTH AMERICA, BY OFFERING, 2015-2025 (USD MILLION)
  • TABLE 57: AI IN HEALTHCARE MARKET IN EUROPE, BY COUNTRY, 2015-2025(USD MILLION)
  • TABLE 58: AI IN HEALTHCARE MARKET IN EUROPE, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 59: AI IN HEALTHCARE MARKET IN EUROPE, BY OFFERING, 2015-2025 (USD MILLION)
  • TABLE 60: AI IN HEALTHCARE MARKET IN APAC, BY COUNTRY, 2015-2025 (USD MILLION)
  • TABLE 61: AI IN HEALTHCARE MARKET IN APAC, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 62: AI IN HEALTHCARE MARKET IN APAC, BY OFFERING, 2015-2025 (USD MILLION)
  • TABLE 63: AI IN HEALTHCARE MARKET IN ROW, BY REGION, 2015-2025 (USD MILLION)
  • TABLE 64: AI IN HEALTHCARE MARKET IN ROW, BY END USER, 2015-2025 (USD MILLION)
  • TABLE 65: AI IN HEALTHCARE MARKET IN ROW, BY OFFERING, 2015-2025 (USD MILLION)

LIST OF FIGURES

  • FIGURE 1: ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET: RESEARCH DESIGN
  • FIGURE 2: MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH
  • FIGURE 3: MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH
  • FIGURE 4: DATA TRIANGULATION
  • FIGURE 5: ASSUMPTIONS FOR THE RESEARCH STUDY
  • FIGURE 6: AI IN HEALTHCARE MARKET, BY OFFERING, 2018 VS. 2025 (USD MILLION)
  • FIGURE 7: AI IN HEALTHCARE MARKET, BY PROCESSOR, 2018 VS. 2025 (USD MILLION)
  • FIGURE 8: AI IN HEALTHCARE MARKET, BY TECHNOLOGY, 2015-2025 (USD MILLION)
  • FIGURE 9: AI IN HEALTHCARE MARKET, BY APPLICATION, 2018 VS. 2025 (USD MILLION)
  • FIGURE 10: AI IN HEALTHCARE MARKET, BY END USER, 2018 VS. 2025 (USD MILLION)
  • FIGURE 11: AI IN HEALTHCARE MARKET, BY REGION, 2018
  • FIGURE 12: GROWING BIG DATA IN HEALTHCARE AND INCREASING ADOPTION OF AI-BASED TOOLS IN HEALTHCARE FACILITIES ARE MAJOR FACTORS DRIVING MARKET GROWTH
  • FIGURE 13: SOFTWARE TO HOLD LARGEST SHARE OF AI IN HEALTHCARE MARKET DURING FORECAST PERIOD
  • FIGURE 14: AI IN HEALTHCARE MARKET FOR MACHINE LEARNING TO HOLD LARGEST SIZE FROM 2018 TO 2025
  • FIGURE 15: GERMANY EXPECTED TO HOLD LARGEST SHARE OF AI IN HEALTHCARE MARKET IN 2018 IN EUROPE
  • FIGURE 16: US TO HOLD LARGEST SHARE OF AI IN HEALTHCARE MARKET IN 2018
  • FIGURE 17: INCREASINGLY LARGE AND COMPLEX DATA SET AND GROWING DEMAND TO REDUCE HEALTHCARE COSTS ARE DRIVING MARKET GROWTH
  • FIGURE 18: TYPES OF HEALTHCARE BREACHES REPORTED TO U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES
  • FIGURE 19: AI IN HEALTHCARE MARKET VALUE CHAIN IN 2017
  • FIGURE 20: SOFTWARE TO HOLD LARGEST SIZE OF AI IN HEALTHCARE MARKET DURING FORECAST PERIOD
  • FIGURE 21: AI IN HEALTHCARE PROCESSOR MARKET FOR GPU TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 22: NORTH AMERICA TO HOLD LARGEST MARKET IN AI IN HEALTHCARE MARKET FOR SOFTWARE DURING FORECAST PERIOD
  • FIGURE 23: MACHINE LEARNING TO HOLD LARGEST SHARE OF AI IN HEALTHCARE MARKET DURING FORECAST PERIOD
  • FIGURE 24: AI IN HEALTHCARE MARKET FOR MEDICAL IMAGING & DIAGNOSTICS TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 25: NORTH AMERICA TO LEAD LIFESTYLE MANAGEMENT & MONITORING APPLICATION DURING FORECAST PERIOD
  • FIGURE 26: NORTH AMERICA TO HOLD LARGEST MARKET IN RESEARCH APPLICATION DURING FORECAST PERIOD
  • FIGURE 27: NORTH AMERICA TO HOLD LARGEST SHARE IN EMERGENCY ROOM & SURGERY APPLICATION IN 2018
  • FIGURE 28: HOSPITALS AND PROVIDERS TO HOLD LARGEST SHARE OF AI IN HEALTHCARE MARKET IN 2018 & 2025
  • FIGURE 29: PRECISION MEDICINE APPLICATION TO WITNESS HIGHEST CAGR IN AI IN HEALTHCARE MARKET FOR PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES DURING FORECAST PERIOD
  • FIGURE 30: CHINA & US ARE EMERGING AS NEW HOT SPOTS IN AI IN HEALTHCARE MARKET
  • FIGURE 31: NORTH AMERICA TO DOMINATE AI IN HEALTHCARE MARKET DURING FORECAST PERIOD
  • FIGURE 32: NORTH AMERICA: SNAPSHOT OF AI IN HEALTHCARE MARKET
  • FIGURE 33: EUROPE: SNAPSHOT OF AI IN HEALTHCARE MARKET
  • FIGURE 34: HOSPITALS & PROVIDERS HELD LARGEST SHARE IN EUROPEAN AI IN HEALTHCARE MARKET IN 2018
  • FIGURE 35: APAC: SNAPSHOT OF AI IN HEALTHCARE MARKET
  • FIGURE 36: SERVICES TO WITNESS HIGHEST CAGR IN AI IN HEALTHCARE MARKET DURING FORECAST PERIOD
  • FIGURE 37: ROW: SNAPSHOT OF AI IN HEALTHCARE MARKET
  • FIGURE 38: KEY DEVELOPMENTS ADOPTED BY TOP PLAYERS IN AI IN HEALTHCARE MARKET FROM 2015 TO MID-2018
  • FIGURE 39: RANKING OF KEY COMPANIES IN AI IN HEALTHCARE MARKET (2017)
  • FIGURE 40: NVIDIA: COMPANY SNAPSHOT
  • FIGURE 41: INTEL: COMPANY SNAPSHOT
  • FIGURE 42: IBM: COMPANY SNAPSHOT
  • FIGURE 43: GOOGLE: COMPANY SNAPSHOT
  • FIGURE 44: MICROSOFT: COMPANY SNAPSHOT
  • FIGURE 45: GE: COMPANY SNAPSHOT
  • FIGURE 46: SIEMENS HEALTHINEERS: COMPANY SNAPSHOT
  • FIGURE 47: MEDTRONIC: COMPANY SNAPSHOT
  • FIGURE 48: MICRON TECHNOLOGY: COMPANY SNAPSHOT
  • FIGURE 49: AWS: COMPANY SNAPSHOT
目次
Product Code: SE 5225

"AI in healthcare market projected to grow at 50.2% CAGR during 2018-2025"

The AI in healthcare market is expected to grow from USD 2.1 billion in 2018 to USD 36.1 billion by 2025, at a CAGR of 50.2% during the forecast period. Increasingly large and complex data set available in the form of big data and growing need to reduce the increasing healthcare cost drive the growth of this market. Improving computing power and declining cost of hardware are other key factors driving this market. However, reluctance among medical practitioners to adopt AI-based technologies and the lack of skilled workforce and ambiguous regulatory guidelines for medical software are among the major factors restraining the growth of the AI in healthcare market.

"Services segment to witness highest growth rate among other offerings during forecast period"

Growing adoption of AI solutions is expected to propel the growth of services segment, which is expected to witness the highest growth. For the successful deployment of AI, there is a need for deployment and integration, and support and maintenance services. Most companies that manufacture and develop AI systems and software provide both online and offline support depending on the applications.

"Machine learning to hold largest market followed by NLP in AI healthcare market"

Machine learning's ability to collect and handle big data and increasing adoption of ML by hospitals, research centers, pharmaceutical companies, and other healthcare institutions to improve patient health are fueling its growth in AI in healthcare market. The growing adoption of NLP is applications such as patient-data and risk analysis, lifestyle management and monitoring, and mental health is propelling the growth of this technology in the market

"Hospitals and providers to hold largest market during forecast period"

The hospitals and providers segment is expected to hold the largest size of AI in healthcare market in terms of end user, during the forecast period. A few major factors responsible for the high share of the hospitals and providers segment include a large number of applications of AI solutions across provider settings; ability of AI systems to improve care delivery, patient experience, and bring down costs; and growing adoption of electronic health records by healthcare organizations. Moreover, AI-based tools, such as voice recognition software and clinical decision support systems, help streamline workflow processes in hospitals, lower cost, improve care delivery, and enhance patient experience.

"North America to witness highest growth from 2018 to 2025"

North America to likely to witness the highest CAGR during the forecast period. The US is considered one of the major contributors in the North American AI in healthcare market. The US is one of the leading countries in the world to adopt AI technology across the continuum of care. Moreover, high consumerization of personal care products-routine check-up medical tools and wearable devices-is further complementing the growth of AI in healthcare market.

In the process of determining and verifying the market size for several segments and subsegments gathered through the secondary research, extensive primary interviews have been conducted with key industry experts in the AI in healthcare marketspace. The break-up of primary participants for the report has been shown below:

  • By Company Type: Tier 1 - 40%, Tier 2 - 25%, and Tier 3 - 35%
  • By Designation: C-level Executives - 45%, Directors - 25%, and Others - 30%
  • By Region: North America - 55%, Europe - 20%, APAC - 15%, and RoW - 10

The report profiles key players in the AI in healthcare market with their respective market ranking analysis. Prominent players profiled in this report are NVIDIA (US), Intel (US), IBM (US), Google (US), Microsoft (US), AWS (US), General Vision (US), GE Healthcare (US), Siemens Healthineers (Germany), Medtronic plc (US), Johnson & Johnson (US), and Koninklijke Philips N.V. (Netherlands).

Research Coverage:

This research report categorizes the global AI market on the basis of offering, technology, end-use application, end user, and geography. The report describes the major drivers, restraints, challenges, and opportunities pertaining to the AI in healthcare market and forecasts the same till 2025.

Key Benefits of Buying the Report:

The report would help leaders/new entrants in this market in the following ways:

  • 1. This report segments the AI in healthcare market comprehensively and provides the closest market size projection for all subsegments across different regions.
  • 2. The report helps stakeholders understand the pulse of the market and provides them with information on key drivers, restraints, challenges, and opportunities for market growth.
  • 3. The report helps stakeholders to understand value-chain of AI in healthcare market along with recent case studies.
  • 4. This report would help stakeholders understand their competitors better and gain more insights to improve their position in the business. The competitive landscape section includes product launch, acquisition, collaboration, expansion, and partnership.

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. YEARS CONSIDERED
  • 1.4. CURRENCY
  • 1.5. STAKEHOLDERS

2. RESEARCH METHODOLOGY

  • 2.1. RESEARCH DATA
    • 2.1.1. SECONDARY AND PRIMARY RESEARCH
      • 2.1.1.1. Key industry insights
    • 2.1.2. SECONDARY DATA
      • 2.1.2.1. List of major secondary sources
      • 2.1.2.2. Secondary sources
    • 2.1.3. PRIMARY DATA
      • 2.1.3.1. Primary interviews with experts
      • 2.1.3.2. Breakdown of primaries
      • 2.1.3.3. Primary sources
  • 2.2. MARKET SIZE ESTIMATION
    • 2.2.1. BOTTOM-UP APPROACH
      • 2.2.1.1. Approach for capturing the market share by bottom-up analysis (demand side)
    • 2.2.2. TOP-DOWN APPROACH
      • 2.2.2.1. Approach for capturing the market share by top-down analysis (supply side)
  • 2.3. MARKET BREAKDOWN AND DATA TRIANGULATION
  • 2.4. RESEARCH ASSUMPTIONS

3. EXECUTIVE SUMMARY

4. PREMIUM INSIGHTS

  • 4.1. ATTRACTIVE OPPORTUNITIES IN AI IN HEALTHCARE MARKET
  • 4.2. AI IN HEALTHCARE MARKET, BY OFFERING
  • 4.3. AI IN HEALTHCARE MARKET, BY TECHNOLOGY
  • 4.4. EUROPE: AI IN HEALTHCARE MARKET, BY END USER AND COUNTRY
  • 4.5. AI IN HEALTHCARE MARKET, BY COUNTRY

5. MARKET OVERVIEW

  • 5.1. INTRODUCTION
  • 5.2. MARKET DYNAMICS
    • 5.2.1. DRIVERS
      • 5.2.1.1. Increasingly large and complex data set
      • 5.2.1.2. Growing demand to reduce healthcare costs
      • 5.2.1.3. Improving computing power and declining hardware cost
      • 5.2.1.4. Growing number of cross-industry partnerships and collaborations
      • 5.2.1.5. Rising need for improvised healthcare services due to imbalance between health workforce and patients
    • 5.2.2. RESTRAINTS
      • 5.2.2.1. Reluctance among medical practitioners to adopt AI-based technologies
      • 5.2.2.2. Lack of skilled AI workforce and ambiguous regulatory guidelines for medical software
    • 5.2.3. OPPORTUNITIES
      • 5.2.3.1. Growing potential of AI-based tools for elderly care
      • 5.2.3.2. Increasing focus on developing human-aware AI systems
    • 5.2.4. CHALLENGES
      • 5.2.4.1. Lack of curated healthcare data
      • 5.2.4.2. Concerns regarding data privacy
      • 5.2.4.3. Lack of interoperability between AI solutions offered by different vendors
  • 5.3. VALUE CHAIN ANALYSIS
  • 5.4. CASE STUDIES
    • 5.4.1. MAYO CLINIC'S CENTRE FOR INDIVIDUALIZED MEDICINE COLLABORATED WITH TEMPUS TO PERSONALIZE CANCER TREATMENT
    • 5.4.2. MICROSOFT COLLABORATED WITH CLEVELAND CLINIC TO IDENTIFY POTENTIAL AT-RISK PATIENTS UNDER ICU CARE
    • 5.4.3. NVIDIA AND MASSACHUSETTS GENERAL HOSPITAL PARTNERED TO USE ARTIFICIAL INTELLIGENCE FOR ADVANCED RADIOLOGY, PATHOLOGY, & GENOMICS
    • 5.4.4. MICROSOFT PARTNERED WITH WEIL CORNELL MEDICINE TO DEVELOP AI-POWERED CHATBOT
    • 5.4.5. PARTNERS HEALTHCARE AND GE HEALTHCARE ENTERED INTO 10-YEAR COLLABORATION FOR INTEGRATING AI ACROSS CONTINUUM OF CARE

6. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET, BY OFFERING

  • 6.1. INTRODUCTION
  • 6.2. HARDWARE
    • 6.2.1. PROCESSOR
      • 6.2.1.1. MPU
      • 6.2.1.2. GPU
      • 6.2.1.3. FPGA
      • 6.2.1.4. ASIC
    • 6.2.2. MEMORY
      • 6.2.2.1. High-bandwidth memory is being developed and deployed for AI applications, independent of its computing architecture
    • 6.2.3. NETWORK
      • 6.2.3.1. NVIDIA (US), Intel (US) and Mellanox Technologies (Israel) are the key providers of network interconnect adapters for AI applications
  • 6.3. SOFTWARE
    • 6.3.1. AI SOLUTIONS
      • 6.3.1.1. On-premises
        • 6.3.1.1.1. Data-Sensitive enterprises prefer on-premises' advanced NLP and ML tools to be used in AI solutions
      • 6.3.1.2. Cloud
        • 6.3.1.2.1. The cloud provides additional flexibility for business operations and real-time deployment ease to companies that are implementing real-time analytics
    • 6.3.2. AI PLATFORM
      • 6.3.2.1. Machine learning framework
        • 6.3.2.1.1. Major tech companies such as Google, IBM, Microsoft are developing and offering their own ML frameworks
      • 6.3.2.2. Application program interface (API)
        • 6.3.2.2.1. APIs are used when programming graphical user interface (GUI) components
  • 6.4. SERVICES
    • 6.4.1. DEPLOYMENT & INTEGRATION
      • 6.4.1.1. Need for deployment and integration services for AI hardware and software solutions is supplementing the growth of services
    • 6.4.2. SUPPORT & MAINTENANCE
      • 6.4.2.1. The ultimate objective of maintenance services is to keep the system at an acceptable standard

7. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET, BY TECHNOLOGY

  • 7.1. INTRODUCTION
  • 7.2. MACHINE LEARNING
    • 7.2.1. DEEP LEARNING
      • 7.2.1.1. Deep learning enables a machine to build a hierarchical representation.
    • 7.2.2. SUPERVISED LEARNING
      • 7.2.2.1. Classification and regression are major segmentation of Supervised learning
    • 7.2.3. REINFORCEMENT LEARNING
      • 7.2.3.1. Reinforcement learning allows systems and software to determine ideal behaviour for maximizing performance of the systems
    • 7.2.4. UNSUPERVISED LEARNING
      • 7.2.4.1. Unsupervised learning include clustering methods consisting of algorithms with unlabelled training data
    • 7.2.5. OTHERS
  • 7.3. NATURAL LANGUAGE PROCESSING
    • 7.3.1. NLP IS WIDELY USED BY THE CLINICAL AND RESEARCH COMMUNITY IN HEALTHCARE
  • 7.4. CONTEXT-AWARE COMPUTING
    • 7.4.1. DEVELOPMENT OF MORE SOPHISTICATED HARD AND SOFT SENSORS HAS ACCELERATED THE GROWTH OF CONTEXT-AWARE COMPUTING
  • 7.5. COMPUTER VISION
    • 7.5.1. COMPUTER VISION TECHNOLOGY HAS SHOWN SIGNIFICANT APPLICATIONS IN SURGERY AND THERAPY

8. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET, BY END-USE APPLICATION

  • 8.1. INTRODUCTION
  • 8.2. PATIENT DATA AND RISK ANALYSIS
    • 8.2.1. GROWTH IN HEALTHCARE DATA HAS ESCALATED PATIENT DATA AND RISK ANALYSIS APPLICATION
  • 8.3. INPATIENT CARE & HOSPITAL MANAGEMENT
    • 8.3.1. DEMAND TO REDUCE THE OPERATIONAL COST IN HOSPITALS TO GENERATE DEMAND FOR AI-BASED IN-PATIENT CARE AND HOSPITAL MANAGEMENT
  • 8.4. MEDICAL IMAGING & DIAGNOSTICS
    • 8.4.1. GROWTH IN MEDICAL IMAGING DATA HAS PROPELLED THE GROWTH OF MEDICAL IMAGING AND DIAGNOSTICS APPLICATION
  • 8.5. LIFESTYLE MANAGEMENT & MONITORING
    • 8.5.1. AI SOLUTIONS FOR LIFESTYLE MANAGEMENT AND MONITORING HELPS PATIENTS IN MAKING HEALTHIER LIFESTYLE CHANGES
  • 8.6. VIRTUAL ASSISTANT
    • 8.6.1. INCREASING DEMAND TO IMPROVE FOLLOW-UP CARE, ESPECIALLY FOR PATIENTS WITH CHRONIC DISEASES, IS DRIVING THE GROWTH OF VIRTUAL ASSISTANTS
  • 8.7. DRUG DISCOVERY
    • 8.7.1. AI TO REDUCE THE TIME AND COST REQUIRED IN DRUG DISCOVERY
  • 8.8. RESEARCH
    • 8.8.1. GROWING ADOPTION OF DIFFERENT TYPES OF AI ALGORITHMS AMONG BIOINFORMATICS RESEARCHERS, ESPECIALLY FOR CLASSIFYING AND MINING THEIR DATABASES, IS THE KEY APPLICATION OF AI IN RESEARCH
  • 8.9. HEALTHCARE ASSISTANCE ROBOTS
    • 8.9.1. HEALTHCARE ASSISTANCE ROBOTS HAVE BEEN ADOPTED IN SEVERAL AREAS THAT DIRECTLY AFFECT PATIENT CARE
  • 8.10. PRECISION MEDICINE
    • 8.10.1. AI IS EXPECTED TO FULFILL THE DEMAND FOR PERSONALIZED TREATMENT PLANS FOR PATIENTS ADMINISTERED WITH PRECISION MEDICINE
  • 8.11. EMERGENCY ROOM & SURGERY
    • 8.11.1. LIMITED WORKFORCE IN EMERGENCY ROOMS AND DEMAND TO SUPPORT CLINICIANS WITH SURGICAL DATA TO DRIVE THE GROWTH OF AI IN EMERGENCY ROOM AND SURGERY
  • 8.12. WEARABLES
    • 8.12.1. WEARABLE DEVICES ARE CLINICALLY USEFUL FOR IMPROVING REAL-TIME MONITORING OF PATIENTS
  • 8.13. MENTAL HEALTH
    • 8.13.1. INCREASE IN MENTAL DISORDERS ACROSS THE WORLD IS THE KEY FACTOR SUPPORTING THE GROWTH OF MENTAL HEALTH APPLICATION

9. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET, BY END USER

  • 9.1. INTRODUCTION
  • 9.2. HOSPITALS AND PROVIDERS
    • 9.2.1. AI CAN BE UTILIZED TO PREDICT AND PREVENT READMISSIONS, AND IMPROVE OPERATIONS AMONG HOSPITALS AND PROVIDERS
  • 9.3. PATIENTS
    • 9.3.1. SMARTPHONE APPLICATIONS AND WEARABLES TO DRIVE THE ADOPTION OF AI AMONG PATIENTS
  • 9.4. PHARMACEUTICAL AND BIOTECHNOLOGY COMPANIES
    • 9.4.1. APPLICATIONS SUCH AS DRUG DISCOVERY, PRECISION MEDICINE, AND RESEARCH TO DRIVE AI IN PHARMACEUTICAL AND BIOTECHNOLOGY COMPANIES
  • 9.5. HEALTHCARE PAYERS
    • 9.5.1. HEALTHCARE PAYERS USE AI TOOLS MAINLY FOR MANAGING RISK, IDENTIFYING CLAIMS TRENDS, AND MAXIMIZING PAYMENT ACCURACY
  • 9.6. OTHERS
    • 9.6.1. PATIENT DATA AND RISK ANALYTICS AND HEALTHCARE ASSISTANCE ROBOTS TO DRIVE THE GROWTH OF AI IN ACOS AND MCOS

10. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET, BY REGION

  • 10.1. INTRODUCTION
  • 10.2. NORTH AMERICA
    • 10.2.1. US
      • 10.2.1.1. High healthcare spending to complement the growth of AI in the US
    • 10.2.2. CANADA
      • 10.2.2.1. Continuous research on NLP and ML across research institutions and universities in Canada propels the AI in healthcare market
    • 10.2.3. MEXICO
      • 10.2.3.1. AI-enabled devices for the healthcare sector have been gaining traction in Mexico
  • 10.3. EUROPE
    • 10.3.1. GERMANY
      • 10.3.1.1. Rising healthcare data generation in the country will be a key driving factor for the growth of the market
    • 10.3.2. UK
      • 10.3.2.1. Large volume of data generated by NHS and digital health solutions have paved the way for AI in the UK
    • 10.3.3. FRANCE
      • 10.3.3.1. Healthcare IT in France has witnessed considerable implementation of AI over the last decade
    • 10.3.4. ITALY
      • 10.3.4.1. Development of electronic health records and aging population to drive the market in Italy
    • 10.3.5. SPAIN
      • 10.3.5.1. Growing awareness of AI in Spain to drive the AI in healthcare market
    • 10.3.6. REST OF EUROPE
  • 10.4. ASIA PACIFIC
    • 10.4.1. CHINA
      • 10.4.1.1. High spending by the government in healthcare and official plans to digitize medical records to drive the AI in healthcare market in China
    • 10.4.2. JAPAN
      • 10.4.2.1. Aging population to drive the growth of AI in Japan
    • 10.4.3. SOUTH KOREA
      • 10.4.3.1. Quality healthcare services and rapid expansion of medical insurance coverage are among the driving factors of AI in healthcare market in South Korea
    • 10.4.4. INDIA
      • 10.4.4.1. Developing IT infrastructure in the country and AI-friendly initiatives by the government are the key factors supporting the growth of AI in India
    • 10.4.5. REST OF ASIA PACIFIC
  • 10.5. REST OF THE WORLD
    • 10.5.1. SOUTH AMERICA
      • 10.5.1.1. Increasing awareness about potential applications of AI in healthcare is driving the growth of the market in South America
    • 10.5.2. MIDDLE EAST AND AFRICA
      • 10.5.2.1. Growing healthcare expenditure in the Middle East and North Africa is a key growth driver of AI in healthcare market

11. COMPETITIVE LANDSCAPE

  • 11.1. OVERVIEW
  • 11.2. RANKING OF PLAYERS, 2017
  • 11.3. COMPETITIVE SCENARIO
    • 11.3.1. PRODUCT DEVELOPMENTS AND LAUNCHES
    • 11.3.2. COLLABORATIONS, PARTNERSHIPS, AND STRATEGIC ALLIANCES
    • 11.3.3. ACQUISITIONS & JOINT VENTURES

12. COMPANY PROFILES (Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*

  • 12.1. KEY PLAYERS
    • 12.1.1. NVIDIA
    • 12.1.2. INTEL
    • 12.1.3. IBM
    • 12.1.4. GOOGLE
    • 12.1.5. MICROSOFT
    • 12.1.6. GENERAL ELECTRIC (GE) COMPANY
    • 12.1.7. SIEMENS HEALTHINEERS (A STRATEGIC UNIT OF THE SIEMENS GROUP)
    • 12.1.8. MEDTRONIC
    • 12.1.9. MICRON TECHNOLOGY
    • 12.1.10. AMAZON WEB SERVICES (AWS)
  • 12.2. OTHER MAJOR COMPANIES
    • 12.2.1. JOHNSON & JOHNSON SERVICES
    • 12.2.2. KONINKLIJKE PHILIPS
    • 12.2.3. GENERAL VISION
  • 12.3. COMPANY PROFILES, BY APPLICATION
    • 12.3.1. PATIENT DATA & RISK ANALYSIS
      • 12.3.1.1. CLOUDMEDX
      • 12.3.1.2. ONCORA MEDICAL
      • 12.3.1.3. ZEPHYR HEALTH
      • 12.3.1.4. SENTRIAN
      • 12.3.1.5. CARESKORE
      • 12.3.1.6. LINGUAMATICS
    • 12.3.2. MEDICAL IMAGING & DIAGNOSTICS
      • 12.3.2.1. ENLITIC
      • 12.3.2.2. BAY LABS
      • 12.3.2.3. BUTTERFLY NETWORKS
      • 12.3.2.4. IMAGIA CYBERNETICS
    • 12.3.3. PRECISION MEDICINE
      • 12.3.3.1. PRECISION HEALTH AI
      • 12.3.3.2. COTA
      • 12.3.3.3. FDNA
    • 12.3.4. DRUG DISCOVERY
      • 12.3.4.1. RECURSION PHARMACEUTICALS
      • 12.3.4.2. ATOMWISE
      • 12.3.4.3. DEEP GENOMICS
      • 12.3.4.4. CLOUD PHARMACEUTICALS
    • 12.3.5. LIFESTYLE MANAGEMENT & MONITORING
      • 12.3.5.1. WELLTOK
      • 12.3.5.2. VITAGENE
      • 12.3.5.3. LUCINA HEALTH
    • 12.3.6. VIRTUAL ASSISTANTS
      • 12.3.6.1. NEXT IT (A VERINT SYSTEMS COMPANY)
      • 12.3.6.2. BABYLON
      • 12.3.6.3. MDLIVE
    • 12.3.7. WEARABLES
      • 12.3.7.1. MAGNEA
      • 12.3.7.2. PHYSIQ
      • 12.3.7.3. CYRCADIA HEALTH
    • 12.3.8. EMERGENCY ROOM & SURGERY
      • 12.3.8.1. CARESYNTAX
      • 12.3.8.2. GAUSS SURGICAL
      • 12.3.8.3. PERCEIVE3D
      • 12.3.8.4. MAXQ AI
    • 12.3.9. IN-PATIENT CARE & HOSPITAL MANAGEMENT
      • 12.3.9.1. QVENTUS
      • 12.3.9.2. WORKFUSION
    • 12.3.10. RESEARCH
      • 12.3.10.1. ICARBONX
      • 12.3.10.2. DESKTOP GENETICS
    • 12.3.11. MENTAL HEALTH
      • 12.3.11.1. GINGER.IO
      • 12.3.11.2. X2AI
      • 12.3.11.3. BIOBEATS
    • 12.3.12. HEALTHCARE ASSISTANCE ROBOTS
      • 12.3.12.1. PILLO
      • 12.3.12.2. CATALIA HEALTH

*Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.

13. APPENDIX

  • 13.1. INSIGHTS FROM INDUSTRY EXPERTS
  • 13.2. DISCUSSION GUIDE
  • 13.3. KNOWLEDGE STORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
  • 13.4. AVAILABLE CUSTOMIZATIONS
  • 13.5. RELATED REPORTS
  • 13.6. AUTHOR DETAILS
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