AI in Oncology

Chapter Outlines

Chapter 2 is an executive summary of key insights captured during our research. It offers a high-level view on the current state of the artificial intelligence in oncology market and its likely evolution in the mid to long-term.

Chapter 3 provides a brief overview of artificial intelligence, machine learning and deep learning. Further, it highlights the classification of AI and its applications in the healthcare and oncology domain. The chapter further features various challenges associated with the adoption of AI in oncology-based software solutions and its future perspectives.

Chapter 4 provides a detailed overview of the overall  market landscape of  companies engaged in the development of AI in oncology- based software solutions, based on several relevant parameters, such as year of establishment, company size (in terms of number of employees), location of headquarters, type of service(s) offered (cancer detection, drug discovery, drug development), type of AI technology used (machine learning, deep learning), type of platform (cloud-based, on-site), type of end-user (hospitals, pharma companies, research institutes).

Chapter 5 provides elaborate profiles of prominent players (based on company competitive analysis score) engaged in offering AI in oncology- based software solutions. Each profile features a brief overview of the company along with information on their year of establishment, number of employees, location of headquarters, key executives, its proprietary platform(s), financial information of the company, AI focused service portfolio, recent developments and an informed future outlook. 

Chapter 6 provides an insightful company competitiveness analysis of AI in oncology- based software providers, based on their supplier strength (in terms of years of experience), portfolio diversity (which takes into account type of service(s), type of AI technology used, type of platform and type of end-user) and portfolio strength (which includes number of platform and target oncological indications).

Chapter 7 provides an in-depth analysis of patents related to AI in oncology- based software solutions filed / granted till date, based on several relevant parameters, such as type of patents, publication year, geographical location / patent jurisdiction, legal status, CPC symbols, type of industry, type of applicants and leading players (in terms of number of patents filed / granted), year-wise trend of filed patent applications and granted patents. In addition, it features a patent valuation analysis which evaluates the qualitative and quantitative aspects of the patents.

Chapter 8 provides an in-depth analysis of the various collaborations and partnerships that have been inked by stakeholders engaged in this domain, during the period 2017-2022. It includes a brief description of the partnership models (including acquisitions, commercialization agreements, technology utilization agreement, technology integration agreement, technology licensing agreement, distribution agreement, product development agreements, research development agreements and service alliance) adopted by stakeholders in this domain. Further, the partnership activity in this domain has been analyzed based on various parameters, such as year of partnership, type of partnership, analysis on most active players and most active partners, type of cancer. Further, the chapter includes a world map representation of all the deals inked in this field in the period 2017-2022, highlighting both intercontinental and intracontinental agreements.

Chapter 9 presents details on various investments received by various players engaged in this domain. Based on several relevant parameters, such as year of investment, number of funding instances, amount invested, type of funding (grant, seed, venture capital, initial public offering, secondary offering, other equity, and debt) and type of investor, along with information on the most active players (in terms of number of funding instances and amount raised), type of investors, most active investors (in terms  of number of funding instances), geographical distribution, area of application, type of cancer and focus area. 

Chapter 10 features an elaborate discussion on implementing blue ocean strategy, covering a strategic plan / guide for emerging software providers to help unlock an uncontested market, featuring thirteen strategic tools, modified in context to AI services in oncology, that can help companies to shift towards a blue ocean strategic market. The chapter also includes detailed analysis on buyer utility map, pioneer-migrator-settler map, and strategic canvas.

Chapter 11 presents an insightful market forecast analysis, highlighting the likely growth of AI services in oncology market till 2035. Additionally, our year-wise projections of the current and future opportunity have further been segmented based on several relevant parameters, such as Type of Cancer (Breast Cancer, Lung Cancer, Prostate Cancer, Colorectal Cancer, Brain Tumor, Solid Malignancies, Other Cancers), Type of End-Users (Hospitals, Pharmaceutical Companies, Research Institutes and Other End-Users), Key Geographical Regions (North America, Europe, Asia-Pacific and Rest of the World).

Chapter 12 is a summary of the entire report. It provides the key takeaways and presents our independent opinion of the AI in oncology market, based on the research and analysis described in the previously mentioned chapters.

Chapter 13 is a collection of interview transcripts of discussions held with various key stakeholders in this market. The chapter provides a brief overview of the companies and details of interviews held with Jon DeVries (Chief Executive Officer, Mirada Medical), Piotr Krajewski (Chief Executive Officer, CancerCenter.AI), Avi Veidman (Chief Executive Officer, Nucleai). Christian Vestergaard Kaltoft (Chief Executive Officer, Visiopharm), David Wilson (Vice President, Marketing and Communications, Enlitic).

Chapter 14 is an appendix, which provides tabulated data and numbers for all the figures provided in the report.

Chapter 15 is an appendix, which provides the list of companies and organizations mentioned in the report.

Table Of Contents

1. PREFACE
1.1. Overview
1.2. Scope of the Report
1.3. Market Segmentation
1.4. Research Methodology
1.5. Key Questions Answered
1.6. Chapter Outlines

2. EXECUTIVE SUMMARY
2.1 Chapter Overview

3. INTRODUCTION
3.1. Chapter Overview
3.2. Overview of Artificial Intelligence
3.3. Types Of Artificial Intelligence
3.4. AI in Healthcare
3.5. Key Challenges Associated with Use of AI in Healthcare Sector
3.6. Future Perspectives

4. MARKET OVERVIEW
4.1. Chapter Overview
4.2. AI in Oncology: Market Landscape of Software providers
4.2.1. Analysis by Year of Establishment
4.2.2. Analysis by Company Size
4.2.3. Analysis by Location of Headquarters (Region-wise)
4.2.4. Analysis by Location of Headquarters (Country-wise)
4.2.5. Analysis by Type of End-User
4.2.6. Analysis by Year of Establishment, Company size and Location of Headquarters

4.3. AI in Oncology: Market Landscape of Software Solutions
4.3.1. Analysis by Type of Service(s) Offered
4.3.2. Analysis by Type of AI Technology Used
4.3.3. Analysis by Type of Platform
4.3.4. Analysis by Type of Service(s) Offered and Type of End-User
4.3.5. Analysis by Type of Platform and Type of AI Technology Used
4.3.6. Analysis by Type of Service(s) Offered, Location of Headquarters and Type of AI Technology Used

5. COMPANY PROFILES 
5.1. Chapter Overview
5.2. Roche Diagnostics
5.2.1. Company Overview
5.2.2. Financial Information
5.2.3. Service Portfolio
5.2.4. Recent Developments and Future Outlook

5.3. IBM Watson Health
5.3.1. Company Overview
5.3.2. Financial Information
5.3.3. Service Portfolio
5.3.4. Recent Developments and Future Outlook

5.4. CancerCenter.AI
5.4.1. Company Overview
5.4.2. Service Portfolio
5.4.3. Recent Development and Future Outlooks

5.5. GE Healthcare
5.5.1. Company Overview
5.5.2. Financial Information
5.5.3. Service Portfolio
5.5.4. Recent Development and Future Outlook

5.6. Concert AI
5.6.1. Company Overview
5.6.2. Service Portfolio
5.6.3. Recent Developments and Future Outlook

5.7. Path AI
5.7.1. Company Overview
5.7.2. Service portfolio
5.7.3. Recent Development and Future Outlook

5.8. Berg
5.8.1. Company Overview
5.8.2. Service Portfolio
5.8.3. Recent Development and Future Outlook

5.9. Median Technologies
5.9.1. Company Overview
5.9.2. Financial Information
5.9.3. Service Portfolio
5.9.4. Recent Development and Future Outlook

5.10. iCAD
5.10.1. Company Overview
5.10.2. Financial Information
5.10.3. Service Portfolio
5.10.4. Recent Developments and Future Outlook

5.11. JLK Inspection
5.11.1. Company Overview
5.11.2. Service Portfolio
5.11.3. Recent Development and Future Outlook

6. COMPANY COMPETITIVENESS ANALYSIS
6.1. Chapter Overview
6.2. Assumptions and Key Parameters
6.3. Methodology
6.3.1. Company Competitiveness: Small Companies in North America
6.3.2. Company Competitiveness: Small Companies in Europe
6.3.3. Company Competitiveness: Small Companies in Asia Pacific
6.3.4. Company Competitiveness: Mid-sized companies in North America
6.3.5. Company Competitiveness: Mid-sized companies in Europe
6.3.6. Company Competitiveness: Mid-sized companies in Asia Pacific
6.3.7. Company Competitiveness: Large companies in North America and Europe

7. PATENT ANALYSIS
7.1. Chapter Overview
7.2. Scope and Methodology
7.3. AI in Oncology: Patent Analysis
7.3.1. Analysis by Type of Patent
7.3.2. Analysis by Patent Publication Year
7.3.3. Analysis by Year-wise Trend of Filed Patent Applications and Granted Patents
7.3.4. Analysis by Jurisdiction
7.3.5. Analysis by Type of Industry
7.3.6. Analysis by Patent Age
7.3.7. Analysis by Legal Status
7.3.8. Analysis by CPC Symbols
7.3.9. Most Active Players: Analysis by Number of Patents
7.3.10. Analysis by Key Inventors

7.4. AI in Oncology: Patent Benchmarking Analysis
7.4.1. Analysis by Patent Characteristics
7.4.2. AI in Oncology: Patent Valuation Analysis

8. PARTNERSHIPS AND COLLABORATIONS
8.1. Chapter Overview
8.2. Partnership Models
8.3 AI in Oncology: Recent Partnerships and Collaborations
8.3.1. Analysis by Year of Partnership
8.3.2. Analysis by Type of Partnership
8.3.3. Analysis by Year and Type of Partnership
8.3.4. Analysis by Company Size and Type of Partnership
8.3.5. Most Active Partners: Analysis by Number of Partnerships
8.3.6. Most Active Players: Analysis by Type of Partnership
8.3.7. Analysis by Type of Cancer 
8.3.8. Analysis by Type of Partner
8.3.9. Analysis by Year and Type of Partner
8.3.10. Intercontinental and Intracontinental Agreements  
8.3.11. Local and International Agreements
8.3.12. Country-Wise Distribution
8.3.13. Analysis by Region

9. FUNDING AND INVESTMENT ANALYSIS
9.1. Chapter Overview
9.2. Types of Funding Models
9.3. AI in Oncology: List of Funding and Investment Analysis
9.3.1. Analysis by Year and Number of Funding Instances 
9.3.2. Analysis by Year and Amount Invested 
9.3.3 Analysis by Type of Funding and Number of Instances 
9.3.4. Analysis by Year, Type of Funding and Amount Invested 
9.3.5. Analysis by Type of Funding and Amount Invested
9.3.6. Analysis by Area of Application  
9.3.7. Analysis by Focus Area 
9.3.8. Analysis by Type of Cancer Indication
9.3.9. Analysis by Geography
9.3.10. Most Active Players by Number of Instances
9.3.11. Most Active Players by Amount Invested
9.3.12. Analysis by Type of Investors
9.3.13. Analysis by Lead Investors

9.4. Summary of Investments

9.5. Concluding Remarks

10. BLUE OCEAN STRATEGY: A STRATEGIC GUIDE FOR START-UPS TO ENTER INTO HIGHLY COMPETITIVE MARKET
10.1. Chapter Overview
10.2. Overview of Blue Ocean Strategy
10.2.1 Red Ocean
10.2.2 Blue Ocean
10.2.3 Difference between Red Ocean Strategy and Blue Ocean Strategy
10.2.4. AI in Oncology: Blue Ocean Strategy and Shift Tools
10.2.4.1. Value Innovation
10.2.4.2. Strategy Canvas
10.2.4.3. Four Action Framework
10.2.4.4. Eliminate-Raise-Reduce-Create (ERRC) Grid
10.2.4.5. Six Path Framework
10.2.4.6. Pioneer-Migrator-Settler (PMS) Map
10.2.4.7. Three Tiers of Noncustomers
10.2.4.8. Sequence of Blue Ocean Strategy
10.2.4.9. Buyer Utility Map
10.2.4.10. The Price Corridor of the Mass
10.2.4.11. Four Hurdles to Strategy Execution
10.2.4.12. Tipping Point Leadership
10.2.4.13. Fair Process

10.3. Conclusion

11. MARKET SIZING AND OPPORTUNITY ANALYSIS
11.1. Chapter Overview
11.2 Key Assumptions and Methodology
11.3. Global Artificial Intelligence in Oncology Market, 2022-2035
11.4. Artificial Intelligence in Oncology Market: Analysis by Type of Cancer, 2022- 2035
11.4.1. Artificial Intelligence in Oncology Market for Breast Cancer, 2022-2035
11.4.2. Artificial Intelligence in Oncology Market for Lung Cancer, 2022-2035
11.4.3. Artificial Intelligence in Oncology Market for Prostate Cancer, 2022-2035
11.4.4. Artificial Intelligence in Oncology Market for Colorectal Cancer, 2022-2035
11.4.5. Artificial Intelligence in Oncology Market for Brain Tumor, 2022-2035
11.4.6. Artificial Intelligence in Oncology Market for Solid Malignancies, 2022-2035
11.4.7. Artificial Intelligence in Oncology Market for Other Cancers, 2022-2035

11.5. Artificial Intelligence in Oncology Market: Analysis by Type of End-User, 2022-2035
11.5.1. Artificial Intelligence in Oncology Market for Hospitals, 2022-2035
11.5.2. Artificial Intelligence in Oncology Market for Pharmaceutical Companies, 2022-2035
11.5.3. Artificial Intelligence in Oncology Market for Research Institutes, 2022-2035
11.5.4. Artificial Intelligence in Oncology Market for Other End-Users, 2022-2035

11.6. Artificial Intelligence in Oncology Market: Analysis by Key Geographical Regions, 2022-2035
11.6.1. Artificial Intelligence in Oncology Market for North America, 2022-2035
11.6.2. Artificial Intelligence in Oncology Market for Europe, 2022-2035
11.6.3. Artificial Intelligence in Oncology Market for Asia Pacific, 2022-2035
11.6.4. Artificial Intelligence in Oncology Market for Rest of the World, 2022-2035

12. CONCLUSION
12.1. Chapter Overview

13. EXECUTIVE INSIGHTS
13.1. Chapter Overview
13.2. Enlitic
13.2.1. Company Snapshot
13.2.2. Interview Transcript: David Wilson (Vice President, Marketing and Communications)

13.3. Nucleai
13.3.1. Company Snapshot
13.3.2. Interview Transcript: Avi Veidman (Chief Executive Officer)

13.4. Mirada Medical
13.4.1. Company Snapshot
13.4.2. Interview Transcript: Jon DeVries (Chief Executive Officer)

13.5. CancerCenter.AI
13.5.1. Company Snapshot
13.5.2. Interview Transcript: Piotr Krajewski (Chief Executive Officer)

13.6. Visiopharm
13.6.1 Company Snapshot
13.6.2 Interview Transcript: Christian Vestergaard Kaltoft (Chief Executive Officer)

14. APPENDIX 1: TABULATED DATA

15. APPENDIX 2: LIST OF COMPANIES AND ORGANIZATIONS

List Of Figures

Figure 2.1 Executive Summary: Market Landscape 
Figure 2.2 Executive Summary: Patent Analysis
Figure 2.3 Executive Summary: Partnerships and Collaboration Analysis
Figure 2.4 Executive Summary: Funding and Investment Analysis
Figure 2.5 Executive Summary: Market Forecast and Opportunity Analysis
Figure 3.1 Historical Evolution of AI  
Figure 3.2 Relationship between AI, ML and DL
Figure 3.3 Type of Artificial Intelligence
Figure 3.4 Artificial Intelligence Software Solutions: Distribution by Oncology-related Field
Figure 3.5 Artificial Intelligence Software Solutions: Distribution by Various Types of Cancers Detected 
Figure 4.1 AI in Oncology Software providers:  Distribution by Year of Establishment
Figure 4.2 AI in Oncology Software providers: Distribution by Company Size
Figure 4.3 AI in Oncology Software providers: Distribution by Location of Headquarters (Region-wise)
Figure 4.4 AI in Oncology Software providers: Distribution by Location of Headquarters (Country-wise)
Figure 4.5 AI in Oncology Software providers: Distribution by Type of End-User
Figure 4.6 AI in Oncology Software providers: Distribution by Year of Establishment, Company Size and Location of Headquarters
Figure 4.7 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered
Figure 4.8 AI in Oncology- based Software Solutions: Distribution by Type of AI Technology Used
Figure 4.9 AI in Oncology- based Software Solutions: Distribution by Type of Platform
Figure 4.10 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered and Type of end-user
Figure 4.11 AI in Oncology Software Solutions: Distribution by Type of Platform and Type of AI Technology Used
Figure 4.12 AI in Oncology-based Software Solutions: Distribution by Type of Service(s) Offered, Location of Headquarters and Type of AI Technology Used
Figure 5.1 Roche Diagnostics: Annual Revenues, 2017-2021 (CHF Billion)
Figure 5.2 Roche Diagnostics: Service Portfolio
Figure 5.3 IBM Watson Health: Annual Revenues, 2017-2021 (USD Billion)
Figure 5.4 IBM Watson Health: Service Portfolio
Figure 5.5 CancerCenter.ai: Service Portfolio
Figure 5.6 GE Healthcare: Annual Revenues, 2017-2021 (USD Billion)
Figure 5.7 PathAI: Service Portfolio
Figure 5.8 BERG: Service Portfolio
Figure 5.9 Median Technologies: Annual Revenues, 2017-2021 (EUR Million)
Figure 5.10 iCAD: Annual Revenues, 2017-2021 (USD Million)
Figure 5.11 iCAD: Distribution of Revenues by Business Units, FY2021 (USD Million)
Figure 5.12 JLK Inspection: Service Portfolio
Figure 6.1 Company Competitiveness Analysis: Small Companies in North America
Figure 6.2 Company Competitiveness Analysis: Small Companies in Europe
Figure 6.3 Company Competitiveness Analysis: Small Companies in Asia Pacific
Figure 6.4 Company Competitiveness Analysis: Mid-sized companies in North America
Figure 6.5 Company Competitiveness Analysis: Mid-sized companies in Europe
Figure 6.6 Company Competitiveness Analysis: Mid-sized companies in Asia Pacific
Figure 6.7 Company Competitiveness Analysis: Large Companies in North America and Europe
Figure 7.1 Patent Analysis: Distribution by Type of Patents
Figure 7.2 Patent Analysis: Cumulative Distribution by Publication Year
Figure 7.3 Patent Analysis: Year-wise Distribution of Filed Patent Applications and Granted Patents
Figure 7.4 Patent Analysis:  Distribution by Jurisdiction
Figure 7.5 Patent Analysis: Cumulative Distribution by Type of Industry
Figure 7.6 Patent Analysis: Distribution by Patent Age
Figure 7.7 Patent Analysis: Distribution by Legal Status
Figure 7.8 Patent Analysis: Distribution by CPC Symbols
Figure 7.9 Leading Industry Players: Distribution by Number of Patents
Figure 7.10 Leading Non-Industry Players: Distribution by Number of Patents
Figure 7.11 Patent Analysis: Distribution by Key Inventors
Figure 7.12 Patent Analysis (Top 10 CPC Symbols): Benchmarking by Leading Industry Players
Figure 7.13 AI in Oncology: Patent Valuation Analysis
Figure 8.1 Partnerships and Collaborations: Distribution by Year of Partnership, 2017- 2022
Figure 8.2 Partnerships and Collaborations: Distribution by Type of Partnership
Figure 8.3 Partnerships and Collaborations: Distribution by Year and Type of Partnership
Figure 8.4 Partnerships and Collaborations: Distribution by Company Size and Type of Partnership
Figure 8.5 Most Active Partners: Distribution by Number of Partnerships
Figure 8.6 Most Active Players: Distribution by Type  of Partnership
Figure 8.7 Partnerships and Collaborations: Distribution by Type of Cancer
Figure 8.8 Partnerships and Collaborations: Distribution by Type of Partner
Figure 8.9 Partnerships and Collaborations: Distribution by Year and Type of Partner
Figure 8.10 Partnerships and Collaborations: Intercontinental and Intracontinental Agreement
Figure 8.11 Partnerships and Collaborations: Local and International Agreement
Figure 8.12 Partnerships and Collaborations: Distribution by Country
Figure 8.13 Partnerships and Collaborations: Distribution by Region
Figure 9.1 Funding and Investment Analysis: Cumulative Year-wise Distribution by Number of Instances, 2017-2022
Figure 9.2 Funding and Investment Analysis: Cumulative Year-wise Distribution by Amount Invested, 2017-2022 (USD Billion)
Figure 9.3 Funding and Investment Analysis: Distribution of Instances by Type of Funding
Figure 9.4 Funding and Investment Analysis: Distribution of Amount Invested by Year and Type of Funding, 2017-2022 (USD Million)
Figure 9.5 Funding and Investment Analysis: Distribution by Amount Invested and Type of Funding (USD Billion)
Figure 9.6 Funding and Investment Analysis: Distribution of Funding Instances by Area of Application
Figure 9.7 Funding and Investment Analysis: Distribution of Instances by Focus Area
Figure 9.8 Funding and Investment Analysis: Distribution of Instances by Type of Cancer
Figure 9.9 Funding and Investment Analysis: Distribution by Geography
Figure 9.10 Most Active Players: Distribution by Number of Instances
Figure 9.11 Most Active Players: Distribution by Amount Invested (USD Million)
Figure 9.12 Funding and Investment Analysis: Distribution by Type of Investors
Figure 9.13 Most Active Investors: Distribution by Number of Instances
Figure 9.14 Funding and Investment Analysis: Summary of Amount Invested, 2017-2022 (USD Billion)
Figure 9.15 Funding and Investment Analysis: Concluding Remarks
Figure 10.1 Red Ocean Strategy vs Blue Ocean Strategy
Figure 10.2 Blue Ocean Strategy: Strategy Canvas
Figure 10.3 Blue Ocean Strategy: Eliminate-Raise-Reduce-Create (ERRC) Grid
Figure 10.4 Blue Ocean Strategy: Pioneer-Migrator-Settler (PMS) Map
Figure 10.5 Blue Ocean Strategy: Three Tiers of Noncustomers
Figure 10.6 Blue Ocean Strategy: Sequence of Blue Ocean Strategy
Figure 10.7 Blue Ocean Strategy: Buyer Utility Map
Figure 10.8 Blue Ocean Strategy: The Price Corridor of the Mass
Figure 11.1 Global Artificial Intelligence in Oncology Market, 2022-2035 (USD Billion)
Figure 11.2 Artificial Intelligence in Oncology Market: Distribution by Type of Cancer, 2022-2035 (USD Billion)
Figure 11.3 Artificial Intelligence in Oncology Market for Breast Cancer, 2022-2035 (USD Billion)
Figure 11.4 Artificial Intelligence in Oncology Market for Lung Cancer, 2022-2035 (USD Billion)
Figure 11.5 Artificial Intelligence in Oncology Market for Prostate Cancer, 2022-2035 (USD Billion)
Figure 11.6 Artificial Intelligence in Oncology Market for Colorectal Cancer, 2022-2035 (USD Billion)
Figure 11.7 Artificial Intelligence in Oncology Market for Brain Tumor, 2022-2035 (USD Billion)
Figure 11.8 Artificial Intelligence in Oncology Market for Solid Malignancies, 2022-2035 (USD Billion)
Figure 11.9 Artificial Intelligence in Oncology Market for Other Cancers, 2022-2035 (USD Billion)
Figure 11.10 Artificial Intelligence in Oncology Market: Distribution by Type of End-User, 2022-2035 (USD Billion)
Figure 11.11 Artificial Intelligence in Oncology Market for Hospitals, 2022-2035 (USD Billion)
Figure 11.12 Artificial Intelligence in Oncology Market for Pharmaceutical Companies, 2022-2035 (USD Billion)
Figure 11.13 Artificial Intelligence in Oncology Market for Research Institutes, 2022-2035 (USD Billion)
Figure 11.14 Artificial Intelligence in Oncology Market for Other End-Users, 2022-2035 (USD Billion)
Figure 11.15 Artificial Intelligence in Oncology Market: Distribution by Geography, 2022-2035 (USD Billion)
Figure 11.16 Artificial Intelligence in Oncology Market for North America, 2022-2035 (USD Billion)
Figure 11.17 Artificial Intelligence in Oncology Market for Europe, 2022-2035 (USD Billion)
Figure 11.18 Artificial Intelligence in Oncology Market for Asia Pacific, 2022-2035 (USD Billion)
Figure 11.19 Artificial Intelligence in Oncology Market for Rest of the World, 2022-2035 (USD Billion)
Figure 12.1 Concluding Remarks: AI in Oncology Market Landscape
Figure 12.2 Concluding Remarks: Patent Analysis
Figure 12.3 Concluding Remarks: Partnerships and Collaborations Analysis
Figure 12.4 Concluding Remarks: Funding and Investment Analysis
Figure 12.5 Concluding Remarks: Market Forecast and Opportunity Analysis

List Of Tables

Table 4.1 AI in Oncology: List of Software providers
Table 4.2 AI in Oncology Software providers: Information on Type of Service(s) Offered
Table 4.3 AI in Oncology Software providers: Information on the Type of AI Technology Used
Table 4.4 AI in Oncology Software providers: Information on Type of Platform
Table 5.1 Roche Diagnostics: Key Highlights
Table 5.2 IBM Watson Health: Key Highlights
Table 5.3 CancerCenter.ai: Key Highlights
Table 5.4 CancerCenter.ai: Recent Developments and Future Outlook
Table 5.5 GE Healthcare: Key Highlights
Table 5.6 GE Healthcare: Recent Developments and Future Outlook
Table 5.7 Concert AI: Key Highlights
Table 5.8 Concert AI: Recent Developments and Future Outlook
Table 5.9 Path AI: Key Highlights
Table 5.10 PathAI: Recent Developments and Future Outlook
Table 5.11 BERG: Key Highlights
Table 5.12 BERG: Recent Developments and Future Outlook
Table 5.13 Median Technologies: Key Highlights
Table 5.14 Median Technologies: Recent Developments and Future Outlook
Table 5.15 iCAD: Key Highlights
Table 5.16 iCAD: Recent Developments and Future Outlook
Table 5.17 JLK Inspection: Key Highlights
Table 7.1 Patent Analysis: CPC Symbols
Table 7.2 Patent Analysis: Most Popular CPC Symbols
Table 7.3 Patent Analysis: List of Top CPC Symbols
Table 7.4 Patent Analysis: Categorization based on Weighted Valuation Scores
Table 7.5 Patent Analysis: List of Relatively High Value Patents
Table 8.1 Partnerships and Collaborations: List of Partnerships and Collaborations, 2017-2022
Table 9.1 AI in Oncology: List of Funding and Investments, 2017-2022
Table 9.2 Funding and Investment Analysis: Summary of Investments (Number of Instances)
Table 9.3 Funding and Investment Analysis: Summary of Investments (Total Amount Invested)
Table 9.4 Funding and Investment Analysis: Summary of Venture Capital Funding
Table 14.1 AI in Oncology Software providers: Distribution by Year of Establishment
Table 14.2 AI in Oncology Software providers: Distribution by Company Size
Table 14.3 AI in Oncology Software providers: Distribution by Location of Headquarters (Region-wise)
Table 14.4 AI in Oncology Software providers: Distribution by Location of Headquarters (Country-wise)
Table 14.5 AI in Oncology Software providers: Distribution by Type of End-User
Table 14.6 AI in Oncology Software providers: Distribution by Year of Establishment, Company Size and Location of Headquarters
Table 14.7 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered
Table 14.8 AI in Oncology- based Software Solutions: Distribution by Type of AI Technology Used
Table 14.9 AI in Oncology- based Software Solutions: Distribution by Type of Platform
Table 14.10 AI in Oncology- based Software Solutions: Distribution by Type of Service(s) Offered and Type of End User
Table 14.11 AI in Oncology-based Software Solutions: Distribution by Type of Platform and Type of AI Technology Used
Table 14.12 Roche Diagnostics: Annual Revenues (CHF Billion)
Table 14.13 IBM Watson Health: Annual Revenues (USD Billion)
Table 14.14 GE Healthcare: Annual Revenues (USD Billion)
Table 14.15 Median Technologies: Annual Revenues (EUR Million)
Table 14.16 iCAD: Annual Revenues (USD Million)
Table 14.17 Patent Analysis: Distribution by Type of Patents
Table 14.18 Patent Analysis: Cumulative Distribution by Publication Year
Table 14.19 Patent Analysis: Year-Wise Distribution of Filed Patent Applications and Granted Patents
Table 14.20 Patent Analysis:  Distribution by Jurisdiction
Table 14.21 Patent Analysis: Cumulative Distribution by Type of Industry
Table 14.22 Patent Analysis: Distribution by Patent Age
Table 14.23 Patent Analysis: Distribution by Legal Status
Table 14.24 Leading Industry Players: Distribution by Number of Patents
Table 14.25 Leading Non-Industry Players: Distribution by Number of Patents
Table 14.26 Patent Analysis: Distribution by Key Inventors
Table 14.27 AI in Oncology: Patent Valuation Analysis
Table 14.28 Partnerships and Collaborations: Distribution by Year of Partnership, 2017- 2022
Table 14.29 Partnerships and Collaborations: Distribution by Type of Partnership
Table 14.30 Partnerships and Collaborations: Distribution by Year and Type of Partnership
Table 14.31 Partnerships and Collaborations: Distribution by Company Size and Type of Partnership
Table 14.32 Most Active Partners: Distribution by Type of Partnership
Table 14.33 Partnerships and Collaborations: Distribution by Type of Cancer
Table 14.34 Partnerships and Collaborations: Distribution by Type of Partner
Table 14.35 Partnerships and Collaborations: Distribution by Year and Type of Partner
Table 14.36 Partnerships and Collaborations: Intercontinental and Intracontinental Agreement
Table 14.37 Partnerships and Collaborations: Local and International Agreement
Table 14.38 Partnerships and Collaborations: Distribution by Country
Table 14.39 Partnerships and Collaborations: Distribution by Region
Table 14.40 Most Active Players: Distribution by number of Partnerships
Table 14.41 Funding and Investment Analysis: Cumulative Year-wise Distribution by Number of Instances, 2017-2022
Table 14.42 Funding and Investment Analysis: Cumulative Year-wise Distribution by Amount Invested, 2017-2022 (USD Billion)
Table 14.43 Funding and Investment Analysis: Distribution of Instances by Type of Funding
Table 14.44 Funding and Investment Analysis: Distribution of Amount Invested and Type of Funding (USD Million)
Table 14.45 Most Active Players: Distribution by Number of Instances
Table 14.46 Most Active Players: Distribution by Amount Invested (USD Million)
Table 14.47 Funding and Investment Analysis: Distribution of Funding Instances by Area of Application
Table 14.48 Funding and Investment Analysis: Distribution of Instances by Focus Area
Table 14.49 Funding and Investment Analysis: Distribution by Geography
Table 14.50 Funding and Investment Analysis: Distribution of Instances by Type of Cancer
Table 14.51 Most Active Investors: Distribution by Number of Instances
Table 14.52 Funding and Investment Analysis: Distribution by Type of Lead Investors
Table 14.53 Funding and Investment Analysis: Summary of Amount Invested, 2017-2022 (USD Million)
Table 14.54 Global Artificial Intelligence in Oncology Market 2022-2035, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.55 Artificial Intelligence in Oncology Market: Distribution by Type of Cancer, 2022-2035
Table 14.56 Artificial Intelligence in Oncology Market for Breast Cancer, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.57 Artificial Intelligence in Oncology Market for Lung Cancer, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.58 Artificial Intelligence in Oncology Market for Prostate Cancer, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.59 Artificial Intelligence in Oncology Market for Colorectal Cancer, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.60 Artificial Intelligence in Oncology Market for Brain Tumor, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.61 Artificial Intelligence in Oncology Market for Solid Malignancies, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.62 Artificial Intelligence in Oncology Market for Other Cancers, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.63 Artificial Intelligence in Oncology Market: Distribution by Type of End-Users, 2022-2035
Table 14.64 Artificial Intelligence in Oncology Market for Hospitals, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.65 Artificial Intelligence in Oncology Market for Pharmaceutical Companies, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.66 Artificial Intelligence in Oncology Market for Research Institutes, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.67 Artificial Intelligence in Oncology Market for Other End-Users, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.68 Artificial Intelligence in Oncology Market: Distribution by Key Geographical Regions, 2022-2035
Table 14.69 Artificial Intelligence in Oncology Market for North America, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.70 Artificial Intelligence in Oncology Market for Europe, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.71 Artificial Intelligence in Oncology Market for Asia Pacific, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)
Table 14.72 Artificial Intelligence in Oncology Market for Rest of the World, Conservative, Base and Optimistic Scenarios, 2022-2035 (USD Billion)

List Of Companies

The following companies and organizations have been mentioned in the report:

1. 500 Startups
2. 6 Dimensions Capital
3. 83North
4. 8VC
5. Affidea
6. Aidence
7. Aidoc
8. AIRA Matrix
9. Alexandria Venture Investments
10. AllianceBernstein
11. Ally Bridge Group
12. Ambra Health
13. AmCad BioMed
14. aMoon Fund
15. Amplify Partners
16. Ankur Capital
17. Apollo Hospital 
18. Arterys
19. ARUP Laboratories 
20. Asset Management Ventures
21. AstraZeneca
22. Athensmed 
23. Atomico
24. Accelerating Technology Purposefully
25. AXA Venture Partners
26. Axilor Ventures
27. Baheya Foundation 
28. Bain Capital Life Sciences
29. BankInvest
30. BEENEXT
31. Benslie Investment Group
32. BERG
33. BioAdvance
34. Biotheranostics 
35. Blackford 
36. Blue Pool Capital
37. Boehringer Ingelheim Venture Fund
38. Borski Fund
39. b-rayZ
40. Breyer Capital
41. BrightEdge 
42. Bristol-Myers Squibb
43. British Business Bank 
44. BVF Partners
45. C.L. David Foundation
46. Cambridge Capital Group
47. CancerCenter.ai
48. Canon Medical Systems 
49. Capitol Health
50. Casdin Capital
51. Catalio Capital Management
52. Charles River Ventures
53. China Merchant Securities International
54. Colorectal Cancer Alliance
55. ConcertAI
56. Connect Ventures
57. Cormorant Asset Management
58. Cosmo Pharmaceuticals
59. Coutts 
60. CPP Investments
61. Cornerstone Total Return Fund 
62. CureMatch
63. CureMetrix
64. D.E. Shaw Research
65. D1 Capital Partners
66. Dana Farber Cancer Institute 
67. Danhua Capital
68. Data Collective Venture Capital
69. Debiopharm Innovation Fund 
70. Declaration Partners
71. Deep Bio
72. DeepHealth
73. DeepMind
74. Delin Ventures
75. Dell Technologies Capital
76. Densitas®
77. DilenyTech 
78. DocPanel
79. Dream Incubator
80. East Hi-tech
81. EcoR1 Capital
82. Emergent Medical Partners
83. Enlitic
84. Envestors
85. European Innovation Council
86. European Investment Bank
87. European Research Council
88. Exor Seeds
89. Farallon Capital Management
90. Fidelity Management and Research
91. Foresite Capital
92. Formation 8
93. DNA Capital
94. Founders Fund
95. Foxconn
96. Franklin Templeton
97. Freenome
98. FUJIFILM 
99. Fund Twenty8
100. GE Healthcare
101. GE Ventures
102. Gebert Rüf Stiftung
103. General Atlantic
104. General Catalyst
105. Generali
106. GenWorks Health
107. Global Ventures 
108. Goldman Sachs
109. Google
110. GRAIL
111. Greycroft
112. Grove Ventures 
113. Guardant Health
114. Guerbet
115. Hanfor Capital Management
116. Harmonix 
117. Health Innovations
118. HealthCare Konnect
119. HealthQuest Capital
120. henQ
121. Hera-MI
122. HERAN Partners
123. Hillhouse Capital Group
124. Hina Group
125. Holland Capital
126. Hologic 
127. Horizon 2020
128. Horizon Ventures
129. Hoxton Ventures
130. HuangPu River Capital
131. Huiying Medical 
132. Ibex Medical Analytics
133. IBM Watson Health
134. iCAD
135. ICBC International
136. Icebreaker.vc
137. Ikonopedia 
138. Illumina
139. IMM Investment
140. Indica Labs 
141. Information Technology Academia Collaboration
142. INKEF Capital
143. Innovate UK
144. Innovation Endeavors
145. Innovation Quarter
146. Inobe
147. Insight Partners
148. Inspirata
149. Institut Curie
150. Intervest
151. IQ Capital
152. iSeed Ventures
153. Janus Henderson Investors
154. JLK Inspection 
155. Johnson & Johnson
156. Kaiku Health
157. Kaiser Permanente
158. Kakao Ventures
159. Kamet Ventures
160. Kansen voor West
161. KdT Ventures
162. Kheiron Medical Technologies
163. Korea Health Industry Development Institute
164. Kinship Trust 
165. KT Investment
166. Laerdal
167. LDPath
168. Legend Capital
169. Leica Biosystems
170. LEO Pharma
171. Lightpoint Medical
172. Liverpool Heart and Chest Hospital 
173. Lucida Medical
174. Luminous Ventures
175. LungLife AI
176. Lunit
177. M Capital 
178. Mamotest 
179. Marubeni Corporation
180. MassMutual Ventures
181. Maverick Ventures
182. Median Technologies 
183. Medical EarlySign
184. Medicover
185. MediPath
186. Medtronic
187. Memorial Sloan Kettering Cancer Center
188. Merck 
189. Metaplanet
190. Metsola Ventures
191. Mirada Medical
192. Mirae Asset Venture Investment
193. MobileODT
194. Mustard Seed 
195. MVision AI
196. Nanox
197. National Center for Research and Development
198. National Education Association 
199. NESTA
200. New Enterprise Associates
201. NewMargin Ventures
202. NewYork-Presbyterian
203. Nice University Hospital 
204. Niramai
205. Northpond Ventures
206. Northwell Health 
207. Northzone
208. Novarad
209. Novo Ventures
210. NSG Ventures
211. Nuard Ventures
212. Nucleai
213. Octopus Ventures
214. OMERS Ventures
215. OMNES
216. Oncora Medical
217. Onward Assist
218. East Netherlands Development Agency
219. Optellum
220. OrbiMed
221. ORI Capital
222. Oxford Technology
223. Paige
224. PathAI
225. Perceptive Advisors
226. Philips 
227. PHS Fund
228. pi Ventures
229. Pillar Companies
230. Ping An Global Voyager Fund
231. Planven Entrepreneur Ventures
232. Polaris Partners
233. Prodeko Ventures
234. Prognica Labs 
235. Proscia
236. PSP Investments
237. Qingsong Fund
238. Qlarity Imaging
239. Quantib
240. Qure.ai
241. QView Medical
242. RA Capital Management
243. Rabo Ventures
244. RAD-AID International
245. RadLink
246. RadNet
247. RaySearch Laboratories
248. Reaktor Ventures
249. Refactor Capital
250. Regal Funds Management
251. Relay Therapeutics
252. Revelation Partners
253. Revolution Growth
254. Rezolut
255. Riverain Technologies 
256. Roche Diagnostics 
257. Roche Venture Fund
258. Rock Springs Capital
259. Sana Kliniken 
260. Sascan Meditech
261. ScreenPoint Medical 
262. Section 32
263. Seno Medical
264. Sequoia Capital
265. Shinhan Investment
266. Siemens Healthineers
267. SK Telecom
268. Skin Analytics 
269. SkinVision
270. SME Instrument
271. SoftBank Vision Fund
272. Soleria Capital
273. Solis Mammography 
274. S28 Capital 
275. St. John's College
276. Stanford University
277. SymphonyAI 
278. SyndicateRoom
279. T. Rowe Price
280. Tara Health
281. Tavistock Group
282. Telix Pharmaceuticals
283. Temasek 
284. Tempus Labs 
285. Tencent
286. The Jagen Group
287. The Netherlands Cancer Institute 
288. The NorthCap University
289. TheraPanacea
290. Therapixel
291. Think.Health
292. Third Rock Ventures
293. Thirona
294. Thorney Investment 
295. TRAF Intercontinental 
296. Tristel
297. Turbine 
298. Tybourne Capital Management
299. National Cancer Institute
300. Innovate UK 
301. Unilabs
302. University of Oxford
303. University of Pittsburgh Medical Center
304. University Radiology 
305. Vaekstfonden
306. Vanedge Capital
307. Vara
308. Varian Medical Systems
309. VentureFounders
310. Verily Life Sciences
311. Vertex Ventures
312. VieCure
313. Atlantic Labs
314. Visiopharm
315. Voima Ventures
316. Volpara Health
317. VoxelCloud
318. Whiterabbit.ai
319. Wondfo Biotech
320. WuXi NextCODE
321. xCures
322. Xingtai People’s Hospital
323. Yizhun Intelligent