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Global AI-Based Digital Pathology Solutions Market is predicted to grow at an 8.6% CAGR during the forecast period for 2025-2034.
Key Industry Insights & Findings from the Report:
Artificial Intelligence (AI) has been proven to be a faster and more effective approach to identifying and assessing pathological characteristics in samples than previous techniques. The drug discovery process is made more efficient and effective by implementing AI, and the diagnosis process can be accelerated and strengthened. In addition, AI aids pathologists in making accurate diagnoses by using data to verify their findings. It can alert them when their conclusions are contrary to what is expected based on the algorithms. As a result, AI-based pathology solutions may become increasingly popular.
By combining Artificial Intelligence (AI) with digital pathology, pathologists can now perform image analytics on a more significant number of slides in a shorter period by combining AI and digital pathology as a validation tool. Pathologists can improve outcomes by focusing on specific regions and improving efficiency accordingly. Digital pathology is enhancing patient engagement with the use of artificial intelligence, with devices and apps providing access to electronic health records, radiology images, etc.
It is becoming increasingly common to use artificial intelligence in healthcare, particularly in pathological diagnosis, to improve patient care. For example, a clinical decision support system is an AI-based tool designed to streamline workflow processes and enhance hospital patient care. The Roche Group announced in October 2021 that it had agreed with PathAI, an artificial intelligence-based pathology technology leader. The agreement outlines the development and distribution of an embedded image analysis workflow to be used by pathologists under this development and distribution contract. An AI-based medical device will be developed as a result of this partnership, which will include a scanner, an assay, a management system, and an algorithm.
Research collaborations and the growth of digital documentation are driving an increase in adoption across all scientific disciplines. The increasing penetration of healthcare IT solutions has boosted the demand for digital pathology solutions. In recent years, many organizations have adopted resolutions to decrease costs, reduce resource bottlenecks, automate processes, and effectively share content. Advancements in technologies, such as microarrays and predictive models, including hybrid models and API algorithms, will also fuel the demand for digital image analysis.
Several factors contribute to the restraints on the market, including the requirement for high capital, which hinders the company's global reach expansion, and a lack of tools necessary to conduct a computational analysis. Also, many factors could limit the market's growth, including a shortage of experienced professionals and a lack of awareness of modern spatial-based technology.
The AI-Based Digital Pathology market is segmented by type of neural network, assay type, type of target disease indication, application, and end-user. All of these segments are subdivided into respective segments. The type of neural network segment has artificial, convolutional, fully convolutional, recurrent neural, and others, respectively. The type of assay category comprises ER assay, HER2 assay, Ki67 assay, PD-L1 assay, PR assay, and other assays. The target disease indication segment includes breast cancer, colorectal cancer, cervical cancer, gastrointestinal cancer, lung cancer, prostate cancer, and other indications. Also, the application segment includes diagnosis, research, and other applications. The last segment is the end-user segment which contains academic institutions, hospitals/healthcare institutions, laboratories/diagnostic institutions, research institutes and other end-users.
In 2021, North America dominated the market with a significant share. A major factor driving North America's share of the AI-based digital pathology market is improved healthcare infrastructure, increased per capita income, and the availability of state-of-the-art research laboratories and institutes. The FDA categorizes DP as a Class II device for primary diagnosis. Digital pathology is poised to become an increasingly vital tool to enhance disease diagnosis and improve the quality of pathology services. The market is expected to benefit from this development across the nation.
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Report Attribute |
Specifications |
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Growth Rate CAGR |
CAGR of 8.6% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Mn,and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
Type of Neural Network, Type Of Assay, Type Of Target Disease Indication, Application, End-User |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico ;The UK; France; Italy; Spain; China; Japan; India; South Korea; South East Asia; South Korea; South East Asia |
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Competitive Landscape |
PathAI, Paige.AI, Akoya Biosciences, Aiforia, aetherAI, CellCarta, Deep Bio Inc., DoMore Diagnostics, PROSCIA, Pramana, Inc., Visiopharm A/S, Roche Tissue Diagnostics, Indica Labs, Ibex Medical Analytics, LDPath, OracleBio Limited, Verily, Mindpeak GmbH, Proscia Inc., SamanTree Medical SA, Tempus AI, Techcyte, Inc., Tribun Health. |
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Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Artificial Intelligence (AI)-based Digital Pathology Market Snapshot
Chapter 4. Global Artificial Intelligence (AI)-based Digital Pathology Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: By Neural Network, Estimates & Trend Analysis
5.1. By Neural Network, & Market Share, 2024 & 2034
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Neural Network:
5.2.1. Artificial Neural Network
5.2.2. Convolutional Neural Network
5.2.3. Fully Convolutional Network
5.2.4. Recurrent Neural Network
5.2.5. Other Neural Networks
Chapter 6. Market Segmentation 2: By Assay Estimates & Trend Analysis
6.1. By Assay & Market Share, 2024 & 2034
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Assay:
6.2.1. ER Assay
6.2.2. HER2 Assay
6.2.3. Ki67 Assay
6.2.4. PD-L1 Assay
6.2.5. PR Assay
6.2.6. Other Assays
Chapter 7. Market Segmentation 3: By Applications Estimates & Trend Analysis
7.1. By Applications & Market Share, 2024 & 2034
7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Applications:
7.2.1. Diagnostics
7.2.2. Research
7.2.3. Other Areas of Application
Chapter 8. Market Segmentation 4: By End-Users Estimates & Trend Analysis
8.1. By End-Users & Market Share, 2024 & 2034
8.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By End-Users:
8.2.1. Academic Institutions
8.2.2. Hospitals/Healthcare Institutions
8.2.3. Laboratories/Diagnostic Institutions
8.2.4. Research Institutes
8.2.5. Other End-Users
Chapter 9. Market Segmentation 5: By Target Disease Indication Estimates & Trend Analysis
9.1. By Target Disease Indication & Market Share, 2024 & 2034
9.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Target Disease Indication:
9.2.1. Breast Cancer
9.2.2. Colorectal Cancer
9.2.3. Cervical Cancer
9.2.4. Gastrointestinal Cancer
9.2.5. Lung Cancer
9.2.6. Prostate Cancer
9.2.7. Other Indications
Chapter 10. Artificial Intelligence (AI)-based Digital Pathology Market Segmentation 6: Regional Estimates & Trend Analysis
10.1. North America
10.1.1. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By Neural Network, 2021-2034
10.1.2. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By Assay, 2021-2034
10.1.3. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By Applications, 2021-2034
10.1.4. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2021-2034
10.1.5. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2021-2034
10.1.6. North America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by country, 2021-2034
10.2. Europe
10.2.1. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, 2021-2034
10.2.2. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, 2021-2034
10.2.3. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, 2021-2034
10.2.4. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2021-2034
10.2.5. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2021-2030
10.2.6. Europe Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2021-2034
10.3. Asia Pacific
10.3.1. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, 2021-2034
10.3.2. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, 2021-2034
10.3.3. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, 2021-2034
10.3.4. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2021-2034
10.3.5. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2021-2034
10.3.6. Asia Pacific Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2021-2034
10.4. Latin America
10.4.1. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, (US$ Million) 2021-2034
10.4.2. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, (US$ Million) 2021-2034
10.4.3. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, (US$ Million) 2021-2034
10.4.4. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2021-2034
10.4.5. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2021-2034
10.4.6. Latin America Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2021-2034
10.5. Middle East & Africa
10.5.1. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Neural Network, (US$ Million) 2021-2034
10.5.2. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Assay, (US$ Million) 2021-2034
10.5.3. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) By Applications, (US$ Million) 2021-2034
10.5.4. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts By End-Users, 2021-2030
10.5.5. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) estimates and forecasts by Target Disease Indication, 2021-2030
10.5.6. Middle East & Africa Artificial Intelligence (AI)-based Digital Pathology Market revenue (US$ Million) by country, 2021-2034
Chapter 11. Competitive Landscape
11.1. Major Mergers and Acquisitions/Strategic Alliances
11.2. Company Profiles
11.2.1. PathAI
11.2.2. Paige.AI
11.2.3. Akoya Biosciences
11.2.4. Aiforia
11.2.5. aetherAI
11.2.6. CellCarta
11.2.7. Deep Bio Inc.
11.2.8. DoMore Diagnostics
11.2.9. PROSCIA
11.2.10. Pramana, Inc.
11.2.11. Visiopharm A/S
11.2.12. Roche Tissue Diagnostics
11.2.13. Indica Labs
11.2.14. Ibex Medical Analytics
11.2.15. LDPath
11.2.16. OracleBio Limited
11.2.17. Verily
11.2.18. Mindpeak GmbH
11.2.19. Proscia Inc.
11.2.20. SamanTree Medical SA
11.2.21. Tempus AI
11.2.22. Techcyte, Inc.
11.2.23. Tribun Health
11.2.24. Other Prominent Players
Global AI-Based Digital Pathology Solutions Market, by Type of Neural Network, (Value US$ Mn)
Global AI-Based Digital Pathology Solutions Market, by Type Of Assay, (Value US$ Mn)
Global AI-Based Digital Pathology Solutions Market, by Type Of Target Disease Indication, (Value US$ Mn)
Global AI-Based Digital Pathology Solutions Market, by Application, (Value US$ Mn)
Global AI-Based Digital Pathology Solutions Market, by End-User, (Value US$ Mn)
Global AI-Based Digital Pathology Solutions Market, by Region, (Value US$ Mn)
North America AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)
Europe AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)
Asia Pacific AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)
Latin America AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)
Middle East & Africa AI-Based Digital Pathology Solutions Market, by Country, (Value US$ Mn)
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
