Key Market Insights
 Presently, close to 80 players offering AI-based digital pathology services are available in the healthcare market which are located across the globe
 In order to tap into the lucrative opportunity associated with AI-based digital pathology, various investment firms have invested over USD 1.7 billion in AI-based digital pathology market space, during the period 2016-2022
 The estimated global demand for AI-based digital pathology is expected to grow at a CAGR of 9,4%, during 2022-2035
 The projected future opportunity for companies engaged in this field is expected to be well distributed across different types of neural networks, types of assay, end-users, areas of applications, target disease indications, and key geographical regions

Table of Contents

1. PREFACE
1.1. Chapter Overview
1.2. Market Segmentations
1.3. Research Methodology
1.4. Key Questions Answered
1.5. Chapter Outlines

2. EXECUTIVE SUMMARY

3. INTRODUCTION
3.1. Chapter Overview
3.2. Artificial Intelligence in Digital Pathology
3.3. Workflow of AI-based Digital Pathology
3.4. Applications of AI-based Digital Pathology Solutions
3.5. Regulatory Requirements Focused on AI-based Digital Pathology:
3.6. Challenges Associated with the Use of AI in Digital Pathology
3.7. Future Perspectives

4. AI-BASED DIGITAL PATHOLOGY: MARKET LANDSCAPE
4.1. Chapter Overview
4.2. AI-based Digital Pathology Providers: Developers Landscape
4.3. AI-based Digital Pathology Providers: Market Landscape

5. AI-BASED DIGITAL PATHOLOGY MARKET: KEY INSIGHTS
5.1. Chapter Overview

6. COMPANY PROFILES
6.1. Chapter Overview
6.2. PathAI
6.2.1. Company Overview
6.2.2. Recent Developments and Future Outlook
6.3. Paige
6.4. Akoya Biosciences
6.5. PROSCIA
6.6. Visiopharm
6.7. Roche Tissue Diagnostics
6.8. Aiforia Technologies
6.9. Indica Labs
6.10. Ibex Medical Analytics

7. COMPANY COMPETITIVENESS ANALYSIS
7.1. Chapter Overview
7.2. Assumptions and Key Parameters
7.3. Methodology
7.4. Benchmarking of Portfolio Strength
7.5. Benchmarking of Funding Strength
7.6. Company Competitiveness Analysis: Small Players
7.7. Company Competitiveness Analysis: Mid-sized Players
7.8. Company Competitiveness Analysis: Large Players

8. FUNDING AND INVESTMENTS
8.1. Chapter Overview
8.2. Types of Funding
8.3. AI-based Digital Pathology: List of Funding and Investments
8.4. Concluding Remarks

9. DEMAND ANALYSIS
9.1. Chapter Overview
9.2. Scope and Methodology
9.3. Global Demand for AI-based Digital Pathology, 2022-2035
9.4. Demand for AI-based Digital Pathology: Analysis by Geography
9.5. Demand for AI-based Digital Pathology: Analysis by Type of End-user
9.6. Concluding Remarks

10. MARKET SIZING AND OPPORTUNITY ANALYSIS
10.1. Chapter Overview
10.2. Forecast Methodology and Key Assumptions
10.3. Global AI-based Digital Pathology Market, 2022-2035
10.4. AI-based Digital Pathology Market: Analysis by Type of Neural Network, 2022 and 2035
10.5. AI-based Digital Pathology Market: Analysis by Type of Assay, 2022 and 2035
10.6. AI-based Digital Pathology Market: Analysis by Type of End-user, 2022 and 2035
10.7. AI-based Digital Pathology Market: Analysis by Area of Application, 2022 and 2035
10.8. AI-based Digital Pathology Market: Analysis by Target Disease Indication, 2022 and 2035
10.9. AI-based Digital Pathology Market: Analysis by Key Geographies, 2022 and 2035

11. CONCLUDING REMARKS

12. EXECUTIVE INSIGHTS
12.1. Chapter Overview
12.2. aetherAI
12.3. CTL Clinitech Lab
12.4. Huron Digital Pathology
12.5. Mindpeak
12.6. Pramana

13. APPENDIX 1: TABULATED DATA

14. APPENDIX II: LIST OF COMPANIES AND ORGANIZATION


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