Table of Content

Table of Contents
1.0 Executive Summary
1.1 Scope of the Research
1.2 Research Methodology
1.3 Research Methodology (continued)

2.0 Industry Overview
2.1 Enhanced Utility of AI Systems Driving Adoption Across the Medical Device Industry
2.2 Broad Spectrum use of AI across Different Healthcare Application Areas
2.3 Innovations in AI-based Medical Devices Contributing to Growing Number of Patents in this Space
2.4 Imaging & Diagnostics Account for the Bulk of AI Patents Across Medical Devices Domain

3.0 Technology Snapshot
3.1 Technology Segmentation Based on Application
3.1.1 Enhancing Screening of Eye Diseases Through AI
3.1.2 AI-based Systems for Detection of Diabetes-associated Retinal Diseases
3.1.3 AI-based Systems for Glaucoma Diagnosis
3.1.4 AI-based Systems for Diagnosis of Different Eye Diseases
3.2 Technology Segmentation Based on Application
3.2.1 Enabling Effective Cancer Diagnosis Through AI-based Platforms
3.2.2 AI-based Systems for Breast Cancer Diagnosis
3.2.3 AI-based Systems for Cancer Diagnosis Through Biological Samples
3.2.4 AI-based Systems for Skin Cancer Diagnosis
3.2.5 Combining AI with Endoscopes for Enhanced Cancer Diagnosis
3.3 Technology Segmentation Based on Application
3.3.1 Improving Patient Health Outcomes Through AI-assisted Patient Monitoring
3.3.2 Wearables for Monitoring Vital Health Parameters
3.3.3 Remote Patient Monitoring System for Respiratory Conditions
3.3.4 AI-driven Platforms for Bedside Patient Monitoring
3.4 Technology Segmentation Based on Application
3.4.1 Emergence of AI-based Medical Imaging as an Indispensable Radiology Tool
3.4.2 Diagnosis of Neurological Diseases Through Medical Imaging Data
3.4.3 AI-based Visualization Systems for Cancer Diagnosis
3.4.4 AI-powered Applications for Chest Imaging
3.4.5 AI-based Medical Imaging Platforms for Detecting Cardiovascular Diseases

4.0 Impact Assessment and Analysis
4.1 Impact of Technology Accelerators and Challenges
4.1.1 Enhanced Accuracy and Early Disease Detection Ability to Spur Market Adoption
4.1.2 Inadequate Curative Data Set and Cyber Security Issues to Impede Systems Use

5.0 Funding Assessment and Growth Opportunity
5.1 Assessment of Government Funding for AI-driven Systems
5.2 Analysis of NIH Funding for AI-driven Systems
5.3 National Institute of Aging Leads the Funding for AI-based Medical Devices Technology Research
5.4 AI-based Medical Imaging Platforms Receive Maximum Funding Compared to Cancer Diagnostics, and Other Application Areas
5.5 Growth Opportunities: Convergence of AI and AR/VR
5.6 Growth Opportunities: Convergence of AI and Electroceuticals
5.7 Growth Opportunities: Convergence of AI and Medical Robotics

6.0 Analyst Insights
6.1 AI to Usher in Enhanced Quality of Clinical Care
6.2 Benchmarking Rubrics
6.3 Impact of AI to be Relatively High for Medical Imaging Analysisas compared to other Application Areas
6.4 Breaking the Iron Triangle in Healthcare Through AI
6.5 Go-to-Market Strategy for Driving AI Adoption in Key Countries
6.6 Future Application Areas for AI in Disease Detection and Management

7.0 Use of AI in Fight Against COVID-19
7.1 AI Enabling Effective Diagnosis of Coronavirus Disease (COVID-19)
7.2 Tracking Disease Spread and Facilitating Effective Treatment Development Through AI

8.0 Key Industry Contacts
8.1 Key Industry Contacts
8.1 Key Industry Contacts (continued)
Legal Disclaimer