Global Artificial Intelligence in Healthcare Market to 2025: 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%

DUBLIN, Jan. 21, 2019 /PRNewswire/ --

The "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" report has been added to ResearchAndMarkets.com's offering.

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 earnings 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.

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).

Key Topics Covered:

1 Introduction

2 Research Methodology

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

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
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

For more information about this report visit https://www.researchandmarkets.com/research/dp4bzk/global_artificial?w=5

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