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Artificial Intelligence in Healthcare Market Global Trends, Market Share, Industry Size, Growth, Opportunities, and Market Forecast 2019 to 2029

Press release   •   Sep 14, 2019 13:08 BST

Global Artificial Intelligence in Healthcare Market is estimated to value over USD 37 billion by 2029 end and is expected to register a CAGR of over 50% during the forecast period 2019 to 2029.

Artificial Intelligence (AI) is mainly applicable in treatment procedures, medication management and drug discovery. Increasing demand for treatments customised according to the requirements of an individual patient is predicted to boost the market growth. Furthermore, AI technology is employed to implement data mining to accelerate healthcare delivery services will increase the adoption of AI technology worldwide. Additionally, the emanation of promising and novel applications for diagnosis and monitoring of diseases will prove to be an integral factor responsible for the significant market growth.

Global Artificial Intelligence in Healthcare Market Overview:Based on technology, the market is bifurcated into natural language processing (NLP), machine learning, context-aware computing and computer vision. Machine learning segment is further sub-segmented as deep learning, supervised learning, unsupervised learning and reinforcement learning.

In terms of offering, the market is categorised as software, hardware and services. The hardware segment further bifurcated into processor and memory while the services segment is further sub-segmented as deployment and integration and support & maintenance.

Depending on the end-use application, the market is bifurcated into in-patient care & hospital, patient data and risk analysis, medical imaging & diagnosis, lifestyle management & monitoring, virtual assistant, healthcare assistant robots, wearable and mental health. Apple watch series 4 was recently granted de novo status making it a class 2 medical device. This has opened new opportunities for the wearables segment to exhibit a soaring market growth globally.

End-user-wise, the market is categorised as patients, hospitals, biotechnology companies and high-tech hospitals & research labs

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Global Artificial Intelligence in Healthcare Market Segmentation:
1. By Region
North America
• Europe
• Asia Pacific
• Latin America
• Rest of the World

2. By Technology• Natural Language Processing (NLP)
• Machine Learningo Deep Learning
o Supervised Learning
o Unsupervised Learning
o Reinforcement Learning

  • Context-Aware Computing
    • Computer Vision
  • 3. By Offering • Software

  • Hardware
    o Processor
    o Memory
  • Services
    o Deployment & Integration
    o Support & Maintenance
  • 4. By End-Use Application• In-Patient Care & Hospital
    • Patient Data and Risk Analysis
    • Medical Imaging & Diagnostics
    • Lifestyle Management & Monitoring
    • Virtual Assistant
    • Healthcare Assistant Robots
    • Wearable
    • Mental Health

    5. By End User• Patients
    • Hospitals
    • Biotechnology Companies
    • High-tech Hospitals and Research Labs

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    Competitive Landscape:• Tier 1 players- established companies in the market with a major market share
    • Tier 2 players
    • Emerging players which are growing rapidly
    • New Entrants

    Key Market Players:• IBM (Watson Health)
    • AiCure
    • APIXIO Inc.
    • iCarbonX
    • Insilico Medicine Inc.
    • Sophia Genetics
    • Welltok
    • Zebra Medical Vision Ltd.

    FutureWise Key Takeaways:• With an ever-increasing patient population, the healthcare database volume shall be consistently increasing thus making the AI technology more crucial for database management
    • Deep learning technology is currently at its nascent stage and further advancements in this technology shall expand the market significantly

    Objectives of the Study:

  • To provide with an exhaustive analysis on the artificial intelligence in healthcare market by region, by technology, by offering, by end-use application, by end user
    • To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints)
    • To evaluate and forecast micro-markets and the overall market
    • To predict the market size, in key regions (along with countries)— North America, Europe, Asia Pacific, Latin America and rest of the world
    • To record evaluate and competitive landscape mapping- product launches, technological advancements, mergers and expansions
    • Profiling of companies to evaluate their market shares, strategies, financials and core competencies
  • Table of Contents

    1. Introduction
    1.1. Scope and Objective
    1.2. Assumptions and Acronyms
    1.3. Forecast Factors
    1.4. Research Methodology

    2. Executive Summary
    2.1. Industry Cluster Analysis
    2.2. Competition Matrix
    2.3. Strategies Recommendations

    3. Market Definition
    3.1. Report Scope (Inclusions & Exclusions)
    3.2. Market Segmentation

    4. Global Artificial Intelligence in Healthcare Market Overview
    4.1. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn)

    5. Key Inclusions
    5.1. Porter’s Five Force analysis
    5.2. Market Dynamics
    5.3. Industry Trends
    5.4. Regulatory Guidelines
    5.5. Opportunities for Artificial Intelligence in Healthcare Market

    6. Competition Dynamics
    6.1. Company Share Analysis (2019)

    7. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 2019-2029 by Technology
    7.1. Key Market Findings
    7.2. Machine Learning
    7.2.1 Deep Learning
    7.2.2 Supervised Learning
    7.2.3 Reinforcement Learning
    7.2.4 Unsupervised Learning

    7.3. Natural Language Processing
    7.4. Context-Aware Computing
    7.5. Computer Vision

    8. Global Artificial Intelligence in Healthcare Market Market Revenue (USD Mn), 2019-2029 by End Use Application
    8.1. Key Market Findings
    8.2. Inpatient Care & Hospital
    8.3. Patient Data and Risk Analysis
    8.4. Medical Imaging & Diagnostics
    8.5. Lifestyle Management & Monitoring
    8.6. Virtual Assistant
    8.7. Healthcare Assistance Robots
    8.8. Wearable
    8.9. Mental Health

    9. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 2019-2029 by Offering
    9.1. Key Market Findings
    9.2. Hardware (Processor, Memory)
    9.3. Computing Architecture (Network)
    9.4. Software
    9.5. Solutions (Cloud, AI Platform, Own ML Frameworks)

    10. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 2019-2029 by End User
    10.1. Key Market Findings
    10.2. Patients
    10.3. Hospitals and Providers
    10.4. Biotechnology Companies
    10.5. High tech Hospitals and Research labs (Healthcare Assistance Robots)

    11. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 2019-2029 by Region
    11.1. Key Market Findings
    11.2. Long Term ROI Segments
    11.3. Revenue Opportunity Influencing Factors
    11.4. Market Revenue (USD Mn) Assessment and Forecast by Region,2029
    11.4.1 North America
    11.4.2 Latin America
    11.4.3 Europe
    11.4.4 Asia Pacific
    11.4.5 Rest of world

    12. North America Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029
    12.1. Key Market Findings
    12.2. Long Term ROI Segments
    12.3. Revenue Opportunity Influencing Factors
    12.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029
    12.4.1 US
    12.4.2 Canada

    13. Latin America Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029
    13.1. Key Market Findings
    13.2. Long Term ROI Segments
    13.3. Revenue Opportunity Influencing Factors
    13.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029
    13.4.1 Brazil
    13.4.2 Mexico
    13.4.3 Argentina
    13.4.4 Rest of Latin America

    14. Europe America Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029
    14.1. Key Market Findings
    14.2. Long Term ROI Segments
    14.3. Revenue Opportunity Influencing Factors
    14.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029
    14.4.1 Germany
    14.4.2 France
    14.4.3 Spain
    14.4.4 UK
    14.4.5 Russia
    14.4.6 Poland
    14.4.7 Rest of Europe

    15. Asia Pacific Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029
    15.1. Key Market Findings
    15.2. Long Term ROI Segments
    15.3. Revenue Opportunity Influencing Factors
    15.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029
    15.4.1 Emerging Asia
    15.4.1.1 China
    15.4.1.2 India
    15.4.1.3 ASEAN-5
    15.4.1.4 Rest of Emerging Asia
    15.4.2 Japan

    16. Rest of World Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029
    16.1. Key Market Findings
    16.2. Long Term ROI Segments
    16.3. Revenue Opportunity Influencing Factors
    16.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029
    16.4.1 Middle East
    16.4.2 South Africa
    16.4.3 North Africa
    16.4.4 Rest of World
    16.4.5 Others

    17. Company Profiles
    17.1. Competition Landscape
    17.2. Global Company Share (USD Mn) Overview, 2019
    17.3. Company Profiles
    17.3.1 Nvidia
    17.3.1.1 Corporate Overview
    17.3.1.2 Financial Performance
    17.3.1.3 Peer Comparison & 3C marketing equation
    17.3.1.4 Company Strategy & Channel Management
    17.3.2 Intel
    17.3.2.1 Corporate Overview
    17.3.2.2 Financial Performance
    17.3.2.3 Peer Comparison & 3C marketing equation
    17.3.2.4 Company Strategy & Channel Management
    17.3.3 Google
    17.3.3.1 Corporate Overview
    17.3.3.2 Financial Performance
    17.3.3.3 Peer Comparison & 3C marketing equation
    17.3.3.4 Company Strategy & Channel Management
    17.3.4 IBM
    17.3.4.1 Corporate Overview
    17.3.4.2 Financial Performance
    17.3.4.3 Peer Comparison & 3C marketing equation
    17.3.4.4 Company Strategy & Channel Management
    17.3.5 Microsoft
    17.3.5.1 Corporate Overview
    17.3.5.2 Financial Performance
    17.3.5.3 Peer Comparison & 3C marketing equation
    17.3.5.4 Company Strategy & Channel Management
    17.3.6 Medtronic
    17.3.6.1 Corporate Overview
    17.3.6.2 Financial Performance
    17.3.6.3 Peer Comparison & 3C marketing equation
    17.3.6.4 Company Strategy & Channel Management
    17.3.7 General Electric
    17.3.7.1 Corporate Overview
    17.3.7.2 Financial Performance
    17.3.7.3 Peer Comparison & 3C marketing equation
    17.3.7.4 Company Strategy & Channel Management
    17.3.8 Amazon Web Services
    17.3.8.1 Corporate Overview
    17.3.8.2 Financial Performance
    17.3.8.3 Peer Comparison & 3C marketing equation
    17.3.8.4 Company Strategy & Channel Management
    17.3.9 Micron Technology
    17.3.9.1 Corporate Overview
    17.3.9.2 Financial Performance
    17.3.9.3 Peer Comparison & 3C marketing equation
    17.3.9.4 Company Strategy & Channel Management
    17.3.10 Pillo
    17.3.10.1 Corporate Overview
    17.3.10.2 Financial Performance
    17.3.10.3 Peer Comparison & 3C marketing equation
    17.3.10.4 Company Strategy & Channel Management
    17.3.11 Catalia Health
    17.3.11.1 Corporate Overview
    17.3.11.2 Financial Performance
    17.3.11.3 Peer Comparison & 3C marketing equation
    17.3.11.4 Company Strategy & Channel Management
    17.3.12 Ginger.Io
    17.3.12.1 Corporate Overview
    17.3.12.2 Financial Performance
    17.3.12.3 Peer Comparison & 3C marketing equation
    17.3.12.4 Company Strategy & Channel Management
    17.3.13 BioBeats
    17.3.13.1 Corporate Overview
    17.3.13.2 Financial Performance
    17.3.13.3 Peer Comparison & 3C marketing equation
    17.3.13.4 Company Strategy & Channel Management
    17.3.14 Icarbonx
    17.3.14.1 Corporate Overview
    17.3.14.2 Financial Performance
    17.3.14.3 Peer Comparison & 3C marketing equation
    17.3.14.4 Company Strategy & Channel Management
    17.3.15 Qventus
    17.3.15.1 Corporate Overview
    17.3.15.2 Financial Performance
    17.3.15.3 Peer Comparison & 3C marketing equation
    17.3.15.4 Company Strategy & Channel Management
    17.3.16 Caresyntax
    17.3.16.1 Corporate Overview
    17.3.16.2 Financial Performance
    17.3.16.3 Peer Comparison & 3C marketing equation
    17.3.16.4 Company Strategy & Channel Management
    17.3.17 Gauss Surgical
    17.3.17.1 Corporate Overview
    17.3.17.2 Financial Performance
    17.3.17.3 Peer Comparison & 3C marketing equation
    17.3.17.4 Company Strategy & Channel Management
    17.3.18 Perceive3d
    17.3.18.1 Corporate Overview
    17.3.18.2 Financial Performance
    17.3.18.3 Peer Comparison & 3C marketing equation
    17.3.18.4 Company Strategy & Channel Management
    17.3.19 Next IT (A Verint Systems Company)
    17.3.19.1 Corporate Overview
    17.3.19.2 Financial Performance
    17.3.19.3 Peer Comparison & 3C marketing equation
    17.3.19.4 Company Strategy & Channel Management
    17.3.20 Atomwise
    17.3.20.1 Corporate Overview
    17.3.20.2 Financial Performance
    17.3.20.3 Peer Comparison & 3C marketing equation
    17.3.20.4 Company Strategy & Channel Management

    18. Research Sources & Primary Verbatim

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