DublinAnd January 21, 2023 /PRNewswire/ – “AI-Based Digital Diseases/AI Pathology Market Breakdown by Neural Network Type, Examination Type, End User Type, Application Region, Target Disease Indicator Type, and Key Geographies, 2022-2035” Report Added ResearchAndMarkets.com an offer.
The “Digital Pathology/Artificial Intelligence Pathology Market” report features an extensive study of the current market landscape and future potential of the AI-based Digital Pathology market. The study features an in-depth analysis, which highlights the capabilities of the various stakeholders involved in providing AI-based digital pathology.
Amidst the ever-increasing demand for pathology services, the concurrent use of technological advances to automate and digitize healthcare procedures is increasing. These advances have accelerated research and clinical diagnosis, as well as improved patient outcomes, in recent years.
Specifically, AI-assisted digital imaging is one such technology, which is revolutionizing the pathology industry by enabling high-throughput scanning of patient samples. To provide more context, AI-driven digital pathology/AI pathology involves collecting, managing, analyzing, and sharing (via digital slides) data in a digital environment.
With this process, digital slides are created by scanning conventional glass slides with a scanning device, which can be viewed on a computer screen or mobile device and provide a high-resolution digital image. Moreover, AI pathology technology offers a viable solution to manage the growing workload in pathology, while ensuring more rapid and consistent diagnostic services and research activities.
Moreover, AI-powered digital pathology solutions (digital pathology scanners and digital pathology software) allow pathologists to examine more cases and provide accurate diagnosis. It is worth noting that digital workflows can speed up processing times, reduce administrative errors, enable remote collaboration, and increase productivity, allowing for significant cost savings.
Given the growing popularity and demand for such solutions in healthcare and scientific research, and the ongoing efforts of AI-powered Digital Pathology Solution Providers/AI Pathology Solution Providers to continue improving/expanding their portfolios, we believe that AI-based digital solutions are likely to Pathology market is developing at a steady pace until 2035.
An executive summary of the insights obtained during our research. It presents a high-level insight into the current state of the Artificial Intelligence-Based Digital Pathology market and its potential evolution over the medium-long term.
A general introduction to AI-based digital pathology, featuring information on AI in digital pathology, AI-based digital pathology workflows, and applications of AI-based digital pathology solutions in healthcare.
A detailed assessment of the overall market landscape of AI-driven digital pathology providers, based on several relevant parameters.
In-depth analysis highlighting contemporary market trends.
Prepare profiles of different leading players who are involved in providing services related to AI-based digital pathology. Each profile contains a brief profile of the company (including information on the year of incorporation, number of employees, location of the headquarters and management team) and details on recent developments and informed future prospects.
Competitive analysis of the company for the various players operating in this field. It highlights the capabilities of industry players (in terms of their expertise across various services related to AI-based digital pathology).
An analysis of the financing and investments made in this field, during the period 2016-2022, based on several relevant criteria, such as the number of cases, the amount invested, the type of financing, the field of application, geography, and information on the most active players. in the field of digital pathology based on artificial intelligence.
Detailed analysis in order to estimate current and future demand for AI-based digital pathology, based on several relevant parameters.
A detailed market forecast analysis, highlighting the potential development of the Artificial Intelligence-Based Digital Pathology market in the short to medium and long term, during the period 2022-2035. In order to account for future uncertainties and to add strength to our model, we presented three market forecast scenarios, namely conservative, normative, and optimistic scenarios, which represent different paths for industry growth.
Frequently Asked Questions
Who are the key players involved in bringing AI-based digital pathology/AI pathology to healthcare?
What geographies have emerged as major hubs for providers of AI-driven digital pathology?
What kind of end-users primarily use AI in digital pathology in their typical workflow?
What type of funding initiatives are commonly reported by stakeholders in this field?
What are the key strategies for emerging players to implement to enter the AI-based Digital Pathology market?
What are the key market trends and driving factors likely to influence the growth of the AI-Based Digital Pathology/Pathology Market?
How is the current and future opportunity likely to be distributed across key market segments?
Main topics covered:
1.1 Chapter Overview
1.2 Market segmentation
1.3 Scientific Research Methods
1.4 Answer the main questions
1.5 Outline of the chapter
2. Executive summary
3.1. Chapter overview
3.2 Artificial intelligence in digital pathology
3.3 AI-based digital pathology workflow
3.4. Applications of digital pathology solutions based on artificial intelligence
3.5 Regulatory Requirements Focusing on AI-Based Digital Pathology:
3.6 Challenges associated with the use of artificial intelligence in digital pathology
3.7 Future Prospects
4. AI-Based Digital Pathology: Market Landscape
4.1 Chapter Overview
4.2 AI-based Digital Pathology Providers: Market Overview
4.3 AI-based Digital Pathology Providers: The Developer Landscape
5. AI-Based Digital Diseases Market: Key Insights
5.1 Chapter Overview
5.1.1. Analysis by type of service and field of application
5.1.2. Analysis by feature type and application area
5.1.3. Analysis by product type and field of application
5.1.4. Analysis by product type and headquarters location
5.1.5. Analysis by company size and headquarters location
6. Company profiles
6.1 Chapter Overview
6.2.1. Company profile
6.2.2. Recent developments and outlook
6.4. Akoya Biological Sciences
6.7 Roche tissue diagnosis
6.8 Euphoria Technologies
6.9 Indica Labs
6.10. Apex Medical Analytics
7. Analysis of the company’s competitiveness
7.1 Chapter Overview
7.2 Assumptions and Key Parameters
7.4. Measurement of wallet strength
7.5 Measuring Funding Strength
7.6. Firm Competitiveness Analysis: Small Players
7.7 Company Competitiveness Analysis: Medium-sized Players
7.8 Company Competitiveness Analysis: Major Players
8. Finance 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 End User Type
9.6 Concluding Remarks
10. Market size and opportunity analysis
10.1. Chapter overview
10.2. Forecasting methodology and key assumptions
10.3. Global AI-Based Digital Pathology Market, 2022-2035
10.4. AI-driven Digital Pathology Market: Analysis by Neural Network Type, 2022 and 2035
10.5. AI-driven Digital Pathology Market: Analysis by Examination Type, 2022 and 2035
10.6. AI-driven Digital Pathology Market: Analysis by End User Type, 2022 and 2035
10.7. Artificial Intelligence-Based Digital Pathology Market: Analysis by Application Area, 2022 and 2035
10.8. AI-driven Digital Pathology Market: Analysis by Target Disease Indicator, 2022 and 2035
10.9. AI-driven Digital Pathology Market: Analysis by Key Geographic Regions, 2022 and 2035
11. Concluding remarks
12. Executive Statistics
12.1. Chapter overview
12.2. Interview transcript: Joe Yeh (CEO and Chairman of the Board)
12.3. CTL Clinicech Lab Interview Transcript: Suraj Pramani (Laboratory Director and Senior Pathologist)
12.4. Huron Digital Pathology Interview Text: Savvas Damaskinos (Vice President for Research and Technology)
12.5. Mindpeak Interview Transcript: Anil Berger (VP, Sales & Marketing)
12.6. Pramana Corresponding Transcript: Scott Wallace (Vice President, Business Development and Strategic Partnerships)
13. Appendix 1: Tabulated data
14. Appendix 2: List of companies and organization
For more information on this report, visit https://www.researchandmarkets.com/r/pnr53l
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