Table of Contents
Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. AI in Medical Coding Market, by Region, 2020-2030 (USD Billion)
1.2.2. AI in Medical Coding Market, by Component, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global AI in Medical Coding Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global AI in Medical Coding Market Dynamics
3.1. AI in Medical Coding Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increasing volume of healthcare data
3.1.1.2. Rapid shift towards remote work and telehealth services
3.1.2. Market Challenges
3.1.2.1. Growing inefficiency in medical billing and revenue cycle management
3.1.2.2. Regulatory and privacy concerns
3.1.3. Market Opportunities
3.1.3.1. Growing advancements in Natural Language Processing (NLP)
3.1.3.2. Rising integration with Electronic Health Records (EHRs)
Chapter 4. Global AI in Medical Coding Market Industry Analysis
4.1. Porter's 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter's 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global AI in Medical Coding Market, by Component
5.1. Market Snapshot
5.2. Global AI in Medical Coding Market by Component, Performance - Potential Analysis
5.3. Global AI in Medical Coding Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. AI in Medical Coding Market, Sub Segment Analysis
5.4.1. In-house
5.4.2. Outsourced
Chapter 6. Global AI in Medical Coding Market, Regional Analysis
6.1. Top Leading Countries
6.2. Top Emerging Countries
6.3. AI in Medical Coding Market, Regional Market Snapshot
6.4. North America AI in Medical Coding Market
6.4.1. U.S. AI in Medical Coding Market
6.4.1.1. Component breakdown estimates & forecasts, 2020-2030
6.4.2. Canada AI in Medical Coding Market
6.5. Europe AI in Medical Coding Market Snapshot
6.5.1. U.K. AI in Medical Coding Market
6.5.2. Germany AI in Medical Coding Market
6.5.3. France AI in Medical Coding Market
6.5.4. Spain AI in Medical Coding Market
6.5.5. Italy AI in Medical Coding Market
6.5.6. Rest of Europe AI in Medical Coding Market
6.6. Asia-Pacific AI in Medical Coding Market Snapshot
6.6.1. China AI in Medical Coding Market
6.6.2. India AI in Medical Coding Market
6.6.3. Japan AI in Medical Coding Market
6.6.4. Australia AI in Medical Coding Market
6.6.5. South Korea AI in Medical Coding Market
6.6.6. Rest of Asia Pacific AI in Medical Coding Market
6.7. Latin America AI in Medical Coding Market Snapshot
6.7.1. Brazil AI in Medical Coding Market
6.7.2. Mexico AI in Medical Coding Market
6.8. Middle East & Africa AI in Medical Coding Market
6.8.1. Saudi Arabia AI in Medical Coding Market
6.8.2. South Africa AI in Medical Coding Market
6.8.3. Rest of Middle East & Africa AI in Medical Coding Market
Chapter 7. Competitive Intelligence
7.1. Key Company SWOT Analysis
7.1.1. Company 1
7.1.2. Company 2
7.1.3. Company 3
7.2. Top Market Strategies
7.3. Company Profiles
7.3.1. International Business Machines (IBM) Corporation
7.3.1.1. Key Information
7.3.1.2. Overview
7.3.1.3. Financial (Subject to Data Availability)
7.3.1.4. Product Summary
7.3.1.5. Recent Developments
7.3.2. Fathom, Inc.
7.3.3. Epic Systems Corporation
7.3.4. Clinion
7.3.5. BUDDI.AI
7.3.6. Cerner Corporation
7.3.7. CodaMetrix
7.3.8. Nuance Communications, Inc
7.3.9. aideo technologies, LLC
7.3.10. Optum, Inc.
Chapter 8. Research Process
8.1. Research Process
8.1.1. Data Mining
8.1.2. Analysis
8.1.3. Market Estimation
8.1.4. Validation
8.1.5. Publishing
8.2. Research Attributes
8.3. Research Assumption