Artificial Intelligence in Healthcare Market with COVID-19 Impact Analysis by Offering, Technology, End-Use Application, End-user and Region – Global…

Dublin, June 25, 2020 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Healthcare Market with Covid-19 Impact Analysis by Offering (Hardware, Software, Services), Technology (Machine Learning, NLP, Context-Aware Computing, Computer Vision), End-Use Application, End User and Region - Global Forecast to 2026" report has been added to ResearchAndMarkets.com's offering.

The AI in healthcare market is expected to be valued at USD 4.9 billion in 2020 and is likely to reach USD 45.2 billion by 2026; it is projected to grow at a CAGR of 44.9% during the forecast period.

The major factors driving the growth of the market are the increasing volume of healthcare data and growing complexities of datasets, the intensifying need to reduce towering healthcare costs, improving computing power and declining hardware costs, a growing number of cross-industry partnerships and collaborations, and rising imbalance between health workforce and patients driving the need for improvised healthcare services.

Another major driving factor fueling the market growth currently is the adoption of this technology by multiple pharmaceutical and biotechnology companies across the world to expedite vaccine or drug development processes for COVID-19. The major restraint for the market is the reluctance among medical practitioners to adopt AI-based technologies and lack of a skilled workforce.

MPU processor segment expected to hold the largest share in AI in healthcare in 2020

An MPU contains all or most of the CPU functions and is the engine that goes into motion when the computer is on. A microprocessor is specially designed to perform arithmetic and logic operations that use small number-holding areas called registers. Typical microprocessor operations include adding, subtracting, comparing two numbers, and fetching numbers. These operations are the result of a set of instructions that are part of the microprocessor design.

AI in the healthcare market for machine learning projected to grow at the highest CAGR during the forecast period

Growing adoption of deep learning in various healthcare applications, especially in the areas of medical imaging, disease diagnostics, and drug discovery, and the use of different sensors and devices to track a patient's health status in real-time are supplementing the growth of the market.

Patient data & risk analysis segment to capture the largest share of AI in the healthcare market

The growth of the patient data & risk analysis segment is attributed to the increasing adoption of EMRs and various advantages offered by AI systems to healthcare service providers, patients, pharmaceuticals companies, and payers.

Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary3.1 Covid-19 Impact Analysis: AI in Healthcare Market3.1.1 Pre-COVID-19 Scenario3.1.2 Realistic Scenario3.1.3 Optimistic Scenario3.1.4 Pessimistic Scenario

4 Premium Insights4.1 Attractive Opportunities in AI in the Healthcare Market4.2 AI in Healthcare Market, by Offering4.3 AI in Healthcare Market, by Technology4.4 Europe: AI in Healthcare Market, by End-user and Country4.5 AI in Healthcare Market, by Country

5 Market Overview5.1 Introduction5.2 Market Dynamics5.2.1 Drivers5.2.1.1 Influx of Large and Complex Healthcare Datasets5.2.1.2 Growing Need to Reduce Healthcare Costs5.2.1.3 Improving Computing Power and Declining Hardware Cost5.2.1.4 Growing Number of Cross-Industry Partnerships and Collaborations5.2.1.5 Rising Need for Improvised Healthcare Services Due to Imbalance Between Health Workforce and Patients5.2.2 Restraints5.2.2.1 Reluctance Among Medical Practitioners to Adopt AI-Based Technologies5.2.2.2 Lack of Skilled AI Workforce and Ambiguous Regulatory Guidelines for Medical Software5.2.3 Opportunities5.2.3.1 Growing Potential of AI-Based Tools for Elderly Care5.2.3.2 Increasing Focus on Developing Human-Aware AI Systems5.2.3.3 Growing Potential of AI-Technology in Genomics, Drug Discovery, and Imaging & Diagnostics to Fight Covid-195.2.4 Challenges5.2.4.1 Lack of Curated Healthcare Data5.2.4.2 Concerns Regarding Data Privacy5.2.4.3 Lack of Interoperability Between AI Solutions Offered by Different Vendors5.3 Value Chain Analysis5.4 Case Studies5.4.1 Mayo Clinic'S Center for Individualized Medicine Collaborated With Tempus to Personalize Cancer Treatment5.4.2 Microsoft Collaborated With Cleveland Clinic to Identify Potential At-Risk Patients Under Icu Care5.4.3 Nvidia and Massachusetts General Hospital Partnered to Use Artificial Intelligence for Advanced Radiology, Pathology, and Genomics5.4.4 Microsoft Partnered With Weil Cornell Medicine to Develop AI-Powered Chatbot5.4.5 Partners Healthcare and GE Healthcare Entered into 10-Year Collaboration for Integrating AI Across Continuum of Care5.4.6 Ultronics, Zebra Medical Vision, Ai2 Incubator, and Fujifilm Sonosite Are Using AI Platform for Enhancing Medical Imaging Analysis5.4.7 Numedii, 4Quant, and Desktop Genetics to Use AI for Research and Development5.4.8 Nuance Launched Dragon Medical Virtual Assistant5.4.9 GE Healthcare Launched Command Center for Emergency Rooms and Surgeries5.4.10 AIserve Offers AI Wearable for Blind and Partially Sighted5.5 Impact of Covid-19 on AI in Healthcare Market

6 Artificial Intelligence in Healthcare Market, by Offering6.1 Introduction6.2 Hardware6.2.1 Processor6.2.1.1 Mpu6.2.1.2 GPU6.2.1.3 Fpga6.2.1.4 Asic6.2.2 Memory6.2.2.1 High-Bandwidth Memory is Being Developed and Deployed for AI Applications, Independent of Its Computing Architecture6.2.3 Network6.2.3.1 Nvidia (US) and Intel (US) Are Key Providers of Network Interconnect Adapters for AI Applications6.3 Software6.3.1 AI Solutions6.3.1.1 On-Premises6.3.1.1.1 Data-Sensitive Enterprises Prefer Advanced On-Premises Nlp and Ml Tools for Use in AI Solutions6.3.1.2 Cloud6.3.1.2.1 Cloud Provides Additional Flexibility for Business Operations and Real-Time Deployment Ease to Companies That Are Implementing Real-Time Analytics6.3.2 AI Platform6.3.2.1 Machine Learning Framework6.3.2.1.1 Major Tech Companies Such as Google, IBM, and Microsoft Are Developing and Offering Ml Frameworks6.3.2.2 Application Program Interface (API)6.3.2.2.1 Apis Are Used During Programming of Graphical User Interface (Gui) Components6.4 Services6.4.1 Deployment & Integration6.4.1.1 Need for Deployment and Integration Services for AI Hardware and Software Solutions is Supplementing Growth of this Segment6.4.2 Support & Maintenance6.4.2.1 Maintenance Services Are Required to Keep the Performance of Systems at An Acceptable Standard

7 Artificial Intelligence in Healthcare Market, by Technology7.1 Introduction7.2 Machine Learning7.2.1 Deep Learning7.2.1.1 Deep Learning Enables Machines to Build Hierarchical Representations7.2.2 Supervised Learning7.2.2.1 Classification and Regression Are Major Segments of Supervised Learning7.2.3 Reinforcement Learning7.2.3.1 Reinforcement Learning Allows Systems and Software to Determine Ideal Behavior for Maximizing Performance of Systems7.2.4 Unsupervised Learning7.2.4.1 Unsupervised Learning Includes Clustering Methods Consisting of Algorithms With Unlabeled Training Data7.2.5 Others7.3 Natural Language Processing7.3.1 Nlp is Widely Used by Clinical and Research Community in Healthcare7.4 Context-Aware Computing7.4.1 Development of More Sophisticated Hard and Soft Sensors Has Accelerated Growth of Context-Aware Computing7.5 Computer Vision7.5.1 Computer Vision Technology Has Shown Significant Applications in Surgery and Therapy

8 Artificial Intelligence in Healthcare Market, by End-Use Application8.1 Introduction8.2 Patient Data and Risk Analysis8.3 Inpatient Care & Hospital Management8.4 Medical Imaging & Diagnostics8.5 Lifestyle Management & Remote Patient Monitoring8.6 Virtual Assistants8.7 Drug Discovery8.8 Research8.9 Healthcare Assistance Robots8.10 Precision Medicine8.11 Emergency Room & Surgery8.12 Wearables8.13 Mental Health8.14 Cybersecurity

9 Artificial Intelligence in Healthcare Market, by End-user9.1 Introduction9.2 Hospitals and Healthcare Providers9.3 Patients9.4 Pharmaceuticals & Biotechnology Companies9.5 Healthcare Payers9.6 Others

10 Artificial Intelligence in Healthcare Market, by Region10.1 Introduction10.2 North America10.3 Europe10.4 Asia-Pacific10.5 Rest of the World

11 Competitive Landscape11.1 Overview11.2 Ranking of Players, 201911.3 Competitive Leadership Mapping11.3.1 Visionary Leaders11.3.2 Dynamic Differentiators11.3.3 Innovators11.3.4 Emerging Companies11.4 Competitive Scenario11.4.1 Product Developments and Launches11.4.2 Collaborations, Partnerships, and Strategic Alliances11.4.3 Acquisitions & Joint Ventures

12 Company Profiles12.1 Key Players12.1.1 Nvidia12.1.2 Intel12.1.3 IBM12.1.4 Google12.1.5 Microsoft12.1.6 General Electric (Ge) Company12.1.7 Siemens Healthineers (A Strategic Unit of Siemens Group)12.1.8 Medtronic12.1.9 Micron Technology12.1.10 Amazon Web Services (Aws)12.2 Right to Win12.3 Other Major Companies12.3.1 Johnson & Johnson Services12.3.2 Koninklijke Philips12.3.3 General Vision12.4 Company Profiles, by Application12.4.1 Patient Data & Risk Analysis12.4.1.1 Cloudmedx12.4.1.2 Oncora Medical12.4.1.3 Anju Life Sciences Software12.4.1.4 Careskore12.4.1.5 Linguamatics12.4.2 Medical Imaging & Diagnostics12.4.2.1 Enlitic12.4.2.2 Lunit12.4.2.3 Curemetrix12.4.2.4 Qure.AI12.4.2.5 Contextvision12.4.2.6 Caption Health12.4.2.7 Butterfly Networks12.4.2.8 Imagia Cybernetics12.4.3 Precision Medicine12.4.3.1 Precision Health AI12.4.3.2 Cota12.4.3.3 FDNA12.4.4 Drug Discovery12.4.4.1 Recursion Pharmaceuticals12.4.4.2 Atomwise12.4.4.3 Deep Genomics12.4.4.4 Cloud Pharmaceuticals12.4.5 Lifestyle Management & Monitoring12.4.5.1 Welltok12.4.5.2 Vitagene12.4.5.3 Lucina Health12.4.6 Virtual Assistants12.4.6.1 Next It (A Verint Systems Company)12.4.6.2 Babylon12.4.6.3 MDLIVE12.4.7 Wearables12.4.7.1 Magnea12.4.7.2 Physiq12.4.7.3 Cyrcadia Health12.4.8 Emergency Room & Surgery12.4.8.1 Caresyntax12.4.8.2 Gauss Surgical12.4.8.3 Perceive 3D12.4.8.4 Maxq AI12.4.9 Inpatient Care & Hospital Management12.4.9.1 Qventus12.4.9.2 Workfusion12.4.10 Research12.4.10.1 Icarbonx12.4.10.2 Desktop Genetics12.4.11 Cybersecurity12.4.11.1 Darktrace12.4.11.2 Cylance12.4.11.3 LexisNexis Risk Solutions12.4.11.4 Securonix12.4.12 Mental Health12.4.12.1 Ginger.Io12.4.12.2 X2Ai12.4.12.3 Biobeats12.4.13 Healthcare Assistance Robots12.4.13.1 Pillo12.4.13.2 Catalia Health

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Artificial Intelligence in Healthcare Market with COVID-19 Impact Analysis by Offering, Technology, End-Use Application, End-user and Region - Global...