CHAPTER 1. INTRODUCTION
1.1. Market Definition
1.2. Executive Summary
1.3. The Scope of the Study
CHAPTER 2. RESEARCH METHODOLOGY
2.1. Secondary Research
2.2. Primary Research
2.3. Analytic Tools and Model
2.4. Economic Indicator
2.4.1 Base Year, Base Currency, Forecasting Period
2.5. Expert Validation
2.6. Study Timeline
CHAPTER 3. MARKET ANALYSIS
3.1. Industry Value Chain Analysis
3.2. Porter's Five Force Analysis
3.2.1. Bargaining Power of Buyers
3.2.2. Bargaining Power of Suppliers
3.2.3. Threats of Substitutes
3.2.4. Threats of New Entrants
3.2.5. Degree of Competition
3.3. PESTLE Analysis
3.3.1. Political
3.3.2. Economical
3.3.3. Social
3.3.4. Technological
3.3.5. Legal
3.3.6. Environmental
3.4. SWOT Analysis
3.4.1. Strengths
3.4.2. Weakness
3.4.3. Opportunities
3.4.4. Threats
3.5. Y-O-Y Analysis
CHAPTER 4. MARKET DYNAMICS
4.1. Market Drivers
4.1.1. Growing need to reduce increasing healthcare costs
4.1.2. Increase in venture capital investments
4.1.3. Big Data in Healthcare
4.1.4. Growing importance of precision medicine
4.1.5. Increase in processing power of AI systems
4.2. Market Restraints & Challenges
4.2.1. Ambiguous regulatory guidelines for medical software
4.2.2. Lack of skilled healthcare professionals
4.2.3. Limitations of AI decision making
4.3. Market Opportunities
4.3.1. The untapped market potential in developing regions
4.3.2. Growing potential of AI-based tools
CHAPTER 5. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET
– BY OFFERING
5.1. Hardware
5.2. Software
5.2.1. AI Platform
5.2.2. Solution
5.3. Services
5.3.1. Support & Maintenance
5.3.2. Deployment and Integration
CHAPTER 6. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET
– BY ALGORITHM
6.1. Context-Aware Processing
6.2. Deep Learning
6.3. Natural Language Processing
6.4. Querying Method
CHAPTER 7. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET
– BY APPLICATION
7.1. Robot-Assisted Surgery
7.2. Virtual Nursing Assistant
7.3. Fraud Detection
7.4. Drug Discovery
7.5. Patient Data and Risk Analytics
7.6. Precision Medicine
7.7. Others
CHAPTER 8. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET
– BY END USER
8.1. Payers
8.2. Healthcare Providers
8.3. Patients
8.4. Pharmaceutical & Biotechnology Companies
8.5. Others
CHAPTER 9. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET
- BY GEOGRAPHY
9.1. Introduction
9.2. North America
9.2.1. U.S.
9.2.2. Canada
9.2.3. Mexico
9.2.4. Costa Rica
9.3. South America
9.3.1. Brazil
9.3.2. Argentina
9.3.3. Chile
9.3.4. Columbia
9.3.5. Others
9.4. Europe
9.4.1. U.K.
9.4.2. Germany
9.4.3. France
9.4.4. Italy
9.4.5. Spain
9.4.6. Russia
9.4.7. Netherlands
9.4.8. Switzerland
9.4.9. Poland
9.4.10. Others
9.5. APAC
9.5.1. China
9.5.2. Japan
9.5.3. India
9.5.4. South Korea
9.5.5. Australia & New Zealand
9.5.6. Malaysia
9.5.7. Singapore
9.5.8. Others
9.6. Middle East & Africa
9.6.1. UAE
9.6.2. Saudi Arabia
9.6.3. Iran
9.6.4. Iraq
9.6.5. Qatar
9.6.6. South Africa
9.6.7. Algeria
9.6.8. Morocco
9.6.9. Nigeria
9.6.10. Egypt
9.6.11. Others
CHAPTER 10. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE
MARKET - COMPANY PROFILES
10.1. Google Inc.
10.2. Microsoft Corporation
10.3. IBM Corporation
10.4. NVIDIA Corporation
10.5. Next IT Corporation
10.6. Koninklijke Philips N.V.
10.7. GE Company
10.8. General Vision Inc.
10.9. ROYAL IMTECH N.V.
10.10. Enlitic Inc.
10.11. iCarbonX
10.12. Intel Corporation
10.13. Weltok Inc.
10.14. Medtronic PLC
10.15. Siemens Healthnieers GmBH
CHAPTER 11. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET
- COMPETITIVE LANDSCAPE
11.1. Market Share Analysis
11.2. Strategies adopted by top companies
11.3. Mergers, Acquisitions, Collaborations & Agreements
CHAPTER 12. MARKET INSIGHTS
12.1. Industry Experts Insights
12.2. Analysts Opinions
12.3. Investment Opportunities
CHAPTER 13. APPENDIX
13.1. List of Tables
13.2. List of Figures
