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AI in Pathology Market Report Scope & overview:

The AI in Pathology Market size was valued at USD 1050.18 million in 2023 and is expected to grow to USD 1915.21 million by 2031 and grow at a CAGR Of 7.8% over the forecast period of 2024-2031.

With the help of the combination of artificial intelligence pathology, pathologists may now adopt image analytics by analyzing more slides in a shorter amount of time. This can assist pathologists in narrowing their focus and enhancing the effectiveness of their results. With devices and applications having access to electronic health records, radiology pictures, and other data, the use of artificial intelligence in pathology will change the whole patient experience and encourage greater patient engagement.

AI in Pathology Market Revenue Analysis

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MARKET DYNAMICS

KEY DRIVERS:

Deep learning algorithms and computer vision techniques have significantly improved in recent years, making it possible for AI models to analyze and interpret medical images with ever-increasing accuracy. There are now more applications for AI in pathology because of the creation of complex AI algorithms that can spot patterns and anomalies in pathology images.

RESTRAIN:

  • Data quality and standardization

  • Cost factors

The creation or procurement of AI software, hardware infrastructure, and continuous maintenance can all be quite expensive when using AI systems in pathology. To justify their adoption, AI systems must carefully consider their return on investment and cost-effectiveness.

OPPORTUNITY:

  •  Workflow Automation

  • Data mining and research

AI systems can examine massive databases, including genomic data and electronic medical records, to find patterns, biomarkers, and new relationships. This promotes pathology research efforts and aids in the creation of innovative diagnostic and therapy strategies.

CHALLENGES:

  • Transparency and comprehensibility

  • Limited data availability for rare diseases

For AI algorithms to perform at their best, they normally need a lot of labeled data. Nevertheless, it can be difficult to get enough labeled data for rare diseases or conditions. Collaborations across healthcare organizations, data-sharing programs, and the creation of transfer learning methodologies to draw on information from related disease fields are all part of the solution to this problem.

IMPACT OF COVID-19

The rapid adoption of AI-based techniques in pathology has been spurred by the need to effectively diagnose and manage COVID-19 cases. To help with the detection and categorization of COVID-19-related pathology findings, such as lung abnormalities on chest radiographs or CT scans, AI algorithms have been created and put to use. The creation of AI models has been employed extensively in COVID-19 research to analyze a sizable amount of histopathology and medical imaging data. Understanding the pathology of the disease and prospective treatments has been made possible thanks to AI algorithms' assistance in recognizing patterns and features in pathology images linked to COVID-19 infection. The pandemic has interfered with research and development in the market for AI in pathology. several clinical trials

IMPACT OF RUSSIA-UKRAINE WAR

The war and its aftermath may cause the international supply chains that support the AI in pathology sector to be disrupted. The development of software and the manufacturing of electrical components both heavily involve Ukraine. Any regional disturbances could cause delays or a lack of essential parts needed for AI pathology systems. Political unrest and hostilities frequently result in economic turbulence, which has an impact on stock market behavior and investment choices. In such a setting, businesses could be reluctant to spend money on AI pathology solutions, which would hinder market expansion or cause it to migrate to more secure geographical areas. The war's effects on the AI pathology market.

IMPACT OF ONGOING RECESSION

During a downturn, money for research and development including AI in pathology may be in short supply. Spending priorities may cause businesses and organizations to cut back on investments in developing technology. This might slow down the creation and uptake of AI applications in pathology. Budget reductions in many industries, including healthcare, are common during recessions. Financial limitations might affect the willingness and capacity of pathology departments to invest in AI technologies. The market for AI in pathology may grow more slowly due to decreased demand.

KEY MARKET SEGMENTATION

By Neural Network Type

  • Convolutional Neural Networks

  • Recurrent Neural Networks

  • Generative Adversarial Networks

  • MVPNet

  • Reinforced Auto Zoom Net

By Product Type

  • Scanners

  • Software

  • Communication Systems

  • Storage Systems

By Type

  • Human Pathology

  • Veterinary Pathology

By End User

  • Pharmaceutical and Biotechnology Companies

  • Hospitals and Reference Laboratories

  • Academic and Research Institutes

By Application

  • Teleconsultation

  • Disease Diagnosis

  • Drug Discovery

  • Training and Education

AI in Pathology Market Segment Analysis

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REGIONAL COVERAGE:

North America

  • USA

  • Canada

  • Mexico

Europe

  • Germany

  • UK

  • France

  • Italy

  • Spain

  • The Netherlands

  • Rest of Europe

Asia-Pacific

  • Japan

  • South Korea

  • China

  • India

  • Australia

  • Rest of Asia-Pacific

The Middle East & Africa

  • Israel

  • UAE

  • South Africa

  • Rest of the Middle East & Africa

Latin America

  • Brazil

  • Argentina

  • Rest of Latin American

Key Players:

The Major Players are Roche, Leica Biosystems, Hamamatsu Photonics, Koninklijke Philips, 3D Hsitech, Apollo Enterprises Imaging, Xifin,  Huron Digital Pathology, Visionpharm, Corista, Indica Labs, Objective Pathology Services, and other players listed in the final report.

Hamamatsu Photonics-Company Financial Analysis

Company Landscape Analysis

AI in Pathology Market Report Scope:

Report Attributes Details
Market Size in 2023  US$ 1050.18 Mn
Market Size by 2031  US$  1915.21 Mn
CAGR   CAGR of 7.8% From 2024 to 2031
Base Year  2023
Forecast Period  2024-2031
Historical Data  2020-2022
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By Neutral Network Type (Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, MVPNet, Reinforced Auto Zoom Net)
• By Product Type (Scanners, Software, Communication Systems, Storage Systems)
• By Type (Human Pathology, Veterinary Pathology)
• By End User (Pharmaceutical and Biotechnology Companies, Hospitals and Reference Laboratories, Academic and Research Institutes)
• By Application (Teleconsultation, Disease Diagnosis, Drug Discovery, Training, and Education)
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America)
Company Profiles Roche, Leica Biosystems, Hamamatsu Photonics, Koninklijke Philips, 3D Hsitech, Apollo Enterprises Imaging, Xifin, Huron Digital Pathology, Visionpharm, Corista, Indica Labs, Objective Pathology Services
Key Drivers • Enhancements in computer Power and Cloud Infrastructure
• Deep learning algorithms
Market Opportunities • Workflow Automation
• Data mining and research

 

Frequently Asked Questions

ANS: The market for AI in pathology market is anticipated to expand by 7.4% from 2023 to 2030

ANS: The AI in pathology market size was valued at USD 974.2 million in 2022.

ANS: Roche, Leica Biosystems, Hamamatsu Photonics, Koninklijke Philips, 3D Hsitech, Apollo Enterprises Imaging, Xifin, Huron Digital Pathology, Visionpharm, Corista, Indica Labs,etc.

ANS: Transparency and comprehensibility and Limited data availability for rare diseases.

ANS: Workflow Automation and Data mining and research.

Table of Contents

1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions

2. Research Methodology

3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges

4. Impact Analysis
4.1 COVID-19 Impact Analysis
4.2 Impact of Ukraine- Russia War
4.3 Impact of Ongoing Recession
4.3.1 Introduction
4.3.2 Impact on major economies
4.3.2.1 US
4.3.2.2 Canada
4.3.2.3 Germany
4.3.2.4 France
4.3.2.5 United Kingdom
4.3.2.6 China
4.3.2.7 Japan
4.3.2.8 South Korea
4.3.2.9 Rest of the World

5. Value Chain Analysis

6. Porter’s 5 forces model

7. PEST Analysis

8. AI in pathology market Segmentation, By Neural Network Type
8.1 Convolutional Neural Networks
8.2 Recurrent Neural Networks
8.3 Generative Adversarial Networks
8.4 MVPNet
8.5 Reinforced Auto Zoom Net

9. AI in Pathology Market Segmentation, By Product Type
9.1 Scanners
9.2 Software
9.3 Communication Systems
9.4 Storage Systems

10. AI in Pathology Market Segmentation, By Type
10.1 Human Pathology
10.2 Veterinary Pathology

11. AI in Pathology Market Segmentation, By End User
11.1 Pharmaceutical and Biotechnology Companies
11.2 Hospitals and Reference Laboratories
113 Academic and Research Institutes

12. AI in Pathology Market Segmentation, By Application
12.1 Teleconsultation
12.2 Disease Diagnosis
12.3 Drug Discovery
12.4 Training and Education

13. Regional Analysis
13.1 Introduction
13.2 North America
13.2.1 North America AI in Pathology Market by Country
13.2.2North America AI in Pathology Market by Neutral Network Type
13.2.3 North America AI in Pathology Market by Product Type
13.2.4 North America AI in Pathology Market by Type
13.2.5 North America AI in Pathology Market by End User
13.2.6 North America AI in Pathology Market by Application
13.2.7 USA
13.2.7.1 USA AI in Pathology Market by Neutral Network Type
13.2.7.2 USA AI in Pathology Market by Product Type
13.2.7.3 USA AI in Pathology Market by Type
13.2.7.4 USA AI in Pathology Market by End User
13.2.7.5 USA AI in Pathology Market by Application
13.2.8 Canada
13.2.8.1 Canada AI in Pathology Market by Neutral Network Type
13.2.8.2 Canada AI in Pathology Market by Product Type
13.2.8.3 Canada AI in Pathology Market by Type
13.2.8.4 Canada AI in Pathology Market by End User
13.2.8.5 Canada AI in Pathology Market by Application
13.2.9 Mexico
13.2.9.1 Mexico AI in Pathology Market by Neutral Network Type
13.2.9.2 Mexico AI in Pathology Market by Product Type
13.2.9.3 Mexico AI in Pathology Market by Type
13.2.9.4 Mexico AI in Pathology Market by End User
13.2.9.5 Mexico AI in Pathology Market by Application
13.3 Europe
13.3.1 Europe AI in Pathology Market by Country
1.3.3.2 Europe AI in Pathology Market by Neutral Network Type
13.3.3 Europe AI in Pathology Market by Product Type
13.3.4 Europe AI in Pathology Market by Type
13.3.5 Europe AI in Pathology Market by End User
13.3.6 Europe AI in Pathology Market by Application
13.3.7 Germany
13.3.7.1 Germany AI in Pathology Market by Neutral Network Type
13.3.7.2 Germany AI in Pathology Market by Product Type
13.3.7.3 Germany AI in Pathology Market by Type
13.3.7.4 Germany AI in Pathology Market by End User
13.3.7.5 Germany AI in Pathology Market by Application
13.3.8 UK
13.3.8.1 UK AI in Pathology Market by Neutral Network Type
13.3.8.2 UK AI in Pathology Market by Product Type
13.3.8.3 UK AI in Pathology Market by Type
13.3.8.4 UK AI in Pathology Market by End User
13.3.8.5 UK AI in Pathology Market by Application
13.3.9 France
13.3.9.1 France AI in Pathology Market by Neutral Network Type
13.3.9.2 France AI in Pathology Market by Product Type
13.3.9.3 France AI in Pathology Market by Type
13.3.9.4 France AI in Pathology Market by End User
13.3.9.5 France AI in Pathology Market by Application
13.3.10 Italy
13.3.10.1 Italy AI in Pathology Market by Neutral Network Type
13.3.10.2 Italy AI in Pathology Market by Product Type
13.3.10.3 Italy AI in Pathology Market by Type
13.3.10.4 Italy AI in Pathology Market by End User
13.3.10.5 Italy AI in Pathology Market by Application
13.3.11 Spain
13.3.11.1 Spain AI in Pathology Market by Neutral Network Type
13.3.11.2 Spain AI in Pathology Market by Product Type
13.3.11.3 Spain AI in Pathology Market by Type
13.3.11.4 Spain AI in Pathology Market by End User
13.3.11.5 Spain AI in Pathology Market by Application
13.3.12 The Netherlands
13.3.12.1 Netherlands AI in Pathology Market by Neutral Network Type
13.3.12.2 Netherlands AI in Pathology Market by Product Type
13.3.12.3 Netherlands AI in Pathology Market by Type
13.3.12.4 Netherlands AI in Pathology Market by End User
13.3.12.5 Netherlands AI in Pathology Market by Application
13.3.13 Rest of Europe
13.3.13.1 Rest of Europe AI in Pathology Market by Neutral Network Type
13.3.13.2 Rest of Europe AI in Pathology Market by Product Type
13.3.13.3 Rest of Europe AI in Pathology Market by Type
13.3.13.4 Rest of Europe AI in Pathology Market by End User
13.3.13.5 Rest of Europe AI in Pathology Market by Application
13.4 Asia-Pacific
13.4.1 Asia Pacific AI in Pathology Market by Country
13.4.2 Asia Pacific AI in Pathology Market by Neutral Network Type
13.4.3 Asia Pacific AI in Pathology Market by Product Type
13.4.4Asia Pacific AI in Pathology Market by Type
13.4.5Asia Pacific AI in Pathology Market by End User
13.4.6 Asia Pacific AI in Pathology Market by Application
13.4.7 Japan
13.4.7.1 Japan AI in Pathology Market by Neutral Network Type
13.4.7.2 Japan AI in Pathology Market by Product Type
13.4.7.3 Japan AI in Pathology Market by Type
13.4.7.4 Japan AI in Pathology Market by End User
13.4.7. 5Japan AI in Pathology Market by Application
13.4.8South Korea
13.4.8.1 South Korea AI in Pathology Market by Neutral Network Type
13.4.8.2 South Korea AI in Pathology Market by Product Type
13.4.8.3 South Korea AI in Pathology Market by Type
13.4.8.4 South Korea AI in Pathology Market by End User
13.4.8.5 South Korea AI in Pathology Market by Application
13.4.9 China
13.4.9.1 China AI in Pathology Market by Neutral Network Type
13.4.9.2 China AI in Pathology Market by Product Type
13.4.9.3 China AI in Pathology Market by Type
13.4.9.4 China AI in Pathology Market by End User
13.4.9.5 China AI in Pathology Market by Application
13.4.10 India
13.4.10.1 India AI in Pathology Market by Neutral Network Type
13.4.10.2 India AI in Pathology Market by Product Type
13.4.10.3 India AI in Pathology Market by Type
13.4.10.4 India AI in Pathology Market by End User
13.4.10.5 India AI in Pathology Market by Application
13.4.11 Australia
13.4.11.1 Australia AI in Pathology Market by Neutral Network Type
13.4.11.2 Australia AI in Pathology Market by Product Type
13.4.11.3 Australia AI in Pathology Market by Type
13.4.11.4 Australia AI in Pathology Market by End User
13.4.11.5 Australia AI in Pathology Market by Application
13.4.12 Rest of Asia-Pacific
13.4.12.1 APAC AI in Pathology Market by Neutral Network Type
13.4.12.2 APAC AI in Pathology Market by Product Type
13.4.12.3 APAC AI in Pathology Market by Type
13.4.12.4 APAC AI in Pathology Market by End User
13.4.12.5 APAC AI in Pathology Market by Application
13.5 The Middle East & Africa
13.5.1 The Middle East & Africa AI in Pathology Market by Country
13.5.2 The Middle East & Africa AI in Pathology Market by Neutral Network Type
13.5.3 The Middle East & Africa AI in Pathology Market by Product Type
13.5.4The Middle East & Africa AI in Pathology Market by Type
13.5.5 The Middle East & Africa AI in Pathology Market by End User
13.5.6The Middle East & Africa AI in Pathology Market by Application
13.5.7 Israel
13.5.7.1 Israel AI in Pathology Market by Neutral Network Type
13.5.7.2 Israel AI in Pathology Market by Product Type
13.5.7.3 Israel AI in Pathology Market by Type
13.5.7.4 Israel AI in Pathology Market by End User
13.5.7.5 Israel AI in Pathology Market by Application
13.5.8 UAE
13.5.8.1 UAE AI in Pathology Market by Neutral Network Type
13.5.8.2 UAE AI in Pathology Market by Product Type
13.5.8.3 UAE AI in Pathology Market by Type
13.5.8.4 UAE AI in Pathology Market by End User
13.5.8.5 UAE AI in Pathology Market by Application
13.5.9South Africa
13.5.9.1 South Africa AI in Pathology Market by Neutral Network Type
13.5.9.2 South Africa AI in Pathology Market by Product Type
13.5.9.3 South Africa AI in Pathology Market by Type
13.5.9.4 South Africa AI in Pathology Market by End User
13.5.9.5 South Africa AI in Pathology Market by Application
13.5.10 Rest of Middle East & Africa
13.5.10.1 Rest of Middle East & Asia AI in Pathology Market by Neutral Network Type
13.5.10.2 Rest of Middle East & Asia AI in Pathology Market by Product Type
13.5.10.3 Rest of Middle East & Asia AI in Pathology Market Type
13.5.10.4 Rest of Middle East & Asia AI in Pathology Market by End User
13.5.10.5 Rest of Middle East & Asia AI in Pathology Market by Application
13.6 Latin America
13.6.1 Latin America AI in Pathology Market by Country
13.6.2 Latin America AI in Pathology Market by Neutral Network Type
13.6.3 Latin America AI in Pathology Market by Product Type
13.6.4 Latin America AI in Pathology Market by Type
13.6.5 Latin America AI in Pathology Market by End User
13.6.6 Latin America AI in Pathology Market by Application
13.6.7 Brazil
13.6.7.1 Brazil AI in Pathology Market by Neutral Network Type
13.6.7.2 Brazil Africa AI in Pathology Market by Product Type
13.6.7.3 Brazil AI in Pathology Market by Type
13.6.7.4 Brazil AI in Pathology Market by End User
13.6.7.5 Brazil AI in Pathology Market by Application
13.6.8 Argentina
13.6.8.1 Argentina AI in Pathology Market by Neutral Network Type
13.6.8.2 Argentina AI in Pathology Market by Product Type
13.6.8.3 Argentina AI in Pathology Market by Type
13.6.8.4 Argentina AI in Pathology Market by End User
13.6.8.5 Argentina AI in Pathology Market by Application
13.6.9 Rest of Latin America
13.6.9.1 Rest of Latin America AI in Pathology Market by Neutral Network Type
13.6.9.2 Rest of Latin America AI in Pathology Market by Product Type
13.6.9.3 Rest of Latin America AI in Pathology Market by Type
13.6.9.4 Rest of Latin America AI in Pathology Market by End User
13.6.9.5 Rest of Latin America AI in Pathology Market by Application

14.Company Profile
14.1 Roche
14.1.1 Market Overview
14.1.2 Financials
14.1.3 Product/Services/Offerings
14.1.4 SWOT Analysis
14.1.5 The SNS View
14.2 Leica Biosystems
14.2.1 Market Overview
14.2.2 Financials
14.2.3 Product /Services/Offerings
14.2.4 SWOT Analysis
14.2.5 The SNS View
14.3 Hamamatsu Photonics
14.3.1 Market Overview
14.3.2 Financials
14.3.3 Product/Services/Offerings
14.3.4 SWOT Analysis
14.3.5 The SNS View
14.4 Koninklijke Philips
14.4.1 Market Overview
14.4.2 Financials
14.4.3 Product/Services/Offerings
14.4.4 SWOT Analysis
14.4.5 The SNS View
14.5 3D Hsitech
14.5.1 Market Overview
14.5.2 Financials
14.5.3 Product/Services/Offerings
14.5.4 SWOT Analysis
14.5.5 The SNS View
14.6 Apollo Enterprises Imaging
14.6.1 Market Overview
14.6.2 Financials
14.6.3 Product/Services/Offerings
14.6.4 SWOT Analysis
14.6.5 The SNS View
14.7 Xifin
14.7.1 Market Overview
14.7.2 Financials
14.7.3 Product/Services/Offerings
14.7.4 SWOT Analysis
14.7.5 The SNS View
14.8 Huron Digital Pathology
14.8.1 Market Overview
14.8.2 Financials
14.8.3 Product/Services/Offerings
14.8.4 SWOT Analysis
14.8.5 The SNS View
14.9 Visionpharm
14.9.1 Market Overview
14.9.2 Financials
14.9.3 Product/Services/Offerings
14.9.4 SWOT Analysis
14.9.5 The SNS View
14.10 Corista
14.10.1 Market Overview
14.10.2 Financials
14.10.3 Product/Services/Offerings
14.10.4 SWOT Analysis
14.10.5 The SNS View
14.11 Indica Labs
14.11.1 Market Overview
14.11.2 Financials
14.11.3 Product/Services/Offerings
14.11.4 SWOT Analysis
14.11.5 The SNS View
14.12 Objective Pathology Services
14.12.1 Market Overview
14.12.2 Financials
14.12.3 Product/Services/Offerings
14.12.4 SWOT Analysis
14.12.5 The SNS View

15. Competitive Landscape
15.1 Competitive Benchmarking
15.2 Market Share Analysis
15.3 Recent Developments

16. USE Cases and Best Practices

17. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

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Data Bank Validation

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