Driven by continuous innovation within pathology subdomains to improve care delivery paradigms across clinical practices, and active R&D efforts undertaken by industry stakeholders, the AI-based digital pathology market is likely to witness significant growth in the coming years

 

Roots Analysis has announced the addition of “AI-based Digital Pathology Market, 2022-2035” report to its list of offerings.

 

The report features an extensive study of the current market landscape, offering an informed opinion on the likely evolution of the market for such services over the next decade. The report features an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this domain. Amongst other elements, the report includes:

§  An executive summary of the key insights captured during our research

§  A brief introduction to important concepts related to AI-based digital pathology, featuring information on workflow of AI-based digital pathology and its primary applications in the healthcare domain

§  A detailed overview of the current market landscape of players engaged in the AI-based digital pathology industry, along with information on their year of establishment, company size, location of headquarters, type of service offered, type of product and area of application

§  An in-depth analysis, highlighting the contemporary market trends, using five schematic representations

§  Elaborate profiles of various prominent players that are currently engaged in the AI-based digital pathology industry

§  An insightful competitiveness analysis of players involved in AI-based digital pathology domain, highlights the capabilities of industry players in terms of their expertise across various services related to AI-based digital pathology

§  An analysis of funding and investments received by players engaged in AI-based digital pathology industry, during the period 2016-2022

§  A detailed analysis to evaluate the current and future demand for AI-based digital pathology services, based on several relevant parameters

§  A detailed market forecast analysis, highlighting the likely growth of the AI-based digital pathology market, for the period 2022-2035

 

§  Type of Neural Network

  • Artificial Neural Network
  • Convolutional Neural Network
  • Fully Convolutional Network
  • Recurrent Neural Network
  • Other Neural Networks

 

§  Type of Assay

  • ER Assay
  • HER2 Assay
  • Ki67 Assay
  • PD-L1 Assay
  • PR Assay
  • Other Type of Assays

 

§  Type of End-user

  • Academic Institutions
  • Hospitals / Healthcare Institutions
  • Laboratories / Diagnostic Institutions
  • Research Institutes
  • Other End-users

 

§  Area of Application

  • Diagnostics
  • Research
  • Other Areas of Application

 

§  Target Disease Indication

  • Breast Cancer
  • Colorectal Cancer
  • Cervical Cancer
  • Gastrointestinal Cancer
  • Lung Cancer
  • Prostate Cancer
  • Other Indications

 

§  Key Geographies

  • North America
  • Europe
  • Asia
  • Latin America
  • Middle East and North Africa
  • Rest of the World

 

§  Key Countries

  • US
  • Canada
  • UK
  • Germany
  • Spain
  • Italy
  • France
  • China
  • Japan
  • South Korea
  • Brazil
  • Saudi Arabia
  • Australia

 

Key companies covered in the report

§  PathAI

§  Paige

§  Akoya Biosciences

§  PROSCIA

§  Visiopharm

§  Roche Tissue Diagnostics

§  Aiforia Technologies

§  Indica Labs

§  Ibex Medical Analytics

 

 

To view more details on this report, click on the link

https://www.rootsanalysis.com/reports/ai-based-digital-pathology-market.html

 

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About Roots Analysis

Roots Analysis is a global leader in the pharma / biotech market research. Having worked with over 750 clients worldwide, including Fortune 500 companies, start-ups, academia, venture capitalists and strategic investors for more than a decade, we offer a highly analytical / data-driven perspective to a network of over 450,000 senior industry stakeholders looking for credible market insights.

 

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Contact:

Ben Johnson

+1 (415) 800 3415

Ben.johnson@rootsanalysis.com