Artificial Intelligence for Histopathology Market

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Artificial Intelligence for Histopathology Market (Model - Deep Learning, and Machine Learning; End User - Pharmaceutical & Biotechnology Companies, Hospitals and Reference Laboratories, and Academic & Research Institutes): Global Industry Analysis, Trends, Size, Share and Forecasts to 2026

  • Published : June, 2021

  • Rep Id : HC08675

  • Category : Healthcare & Medical Devices

  • Status : Published

A recent report published by Infinium Global Research on artificial intelligence for histopathology market provides in-depth analysis of segments and sub-segments in the global as well as regional artificial intelligence for the histopathology market. The study also highlights the impact of drivers, restraints, and macro indicators on the global and regional artificial intelligence for histopathology market over the short term as well as long term. The report is a comprehensive presentation of trends, forecast and dollar values of global artificial intelligence for histopathology market. According to the report, the global artificial intelligence for histopathology market was nearly worth USD 100 million in 2020 and is expected to reach USD 500 Million by 2026, growing with a CAGR of 30% over the forecast period of 2020-2026.

 

Market Insight

Histopathology is a gold standard for disease diagnosis, and advances in artificial intelligence will increase the accuracy of this technique. Artificial intelligence for histopathology can be applied to detect and count cells. It can also be applied to detect segmentation and classify tissues whether it is healthy or diseased. A key benefit of such artificial technology is that it can be applied to whole slide imaging, where the AI can automatically identify patterns in a whole slide.

 

The pandemic has had a significant impact on clinical services, including cancer pathways. Pathologists are working remotely in many circumstances to protect themselves, colleagues, and the delivery of clinical services. The effects of COVID-19 on research and clinical trials have also been significant with changing protocols. Pathology is a vital part of cancer and other diagnostic pathways, being a core component in 70% of clinical interventions. A prior to the COVID-19 pandemic, histopathology capacity was not keeping pace with year-on-year increases in demand. In this case, AI gaining traction. There are several AI tools on the ‘roadmap’ to full diagnostic use and some have regulatory clearance too. With further evidence, AI could provide double reporting such as has been outlined as a possibility in mammography screening, providing resilience to services when pathologists are not available, and creating further efficiency gains. AI-based computational histopathology increases both the accuracy and availability of high-quality health care to patients in many medical fields. The primary forces and limitations in this field are a shortage of experienced pathologists and the limitation of global health care resources.

 

AI has the ability to handle the gigantic quantity of data created throughout the patient care lifecycle to improve pathologic diagnosis, classification, prediction, and prognostication of diseases. Histopathology is the cornerstone of cancer care. The need for accuracy in the histopathologic diagnosis of cancer is increasing as personalized cancer therapy requires accurate biomarker assessment. The integration of machine learning into routine care will be a milestone for the healthcare sector, and histopathology is right at the center of this revolution. Recent studies have demonstrated that applications of machine learning in pathology significantly improves metastases detection in lymph nodes, Ki67 scoring in breast cancer, Gleason grading in prostate cancer, and tumor-infiltrating lymphocyte (TIL) scoring in melanoma. With continual innovation in AI-based pathologies, AI could detect 0.2mm tumors or tumors made up of less than 200 cells. The research found that a deep learning system has achieved an accuracy rate of 0.7 in comparison to 0.61 by pathologists. However, data sets for learning are expensive, again there is a risk of bias from the training data and no transparency into the decision process which affects the growth of the market. Moreover, technological advancement in AI for histopathology will provide a significant growth opportunity for the market.

 

North America dominates the artificial intelligence for the histopathology market. The growing prevalence of cancer, rising demand for quality diagnostics, the introduction of favorable reimbursement policies, and the implementation of favorable initiatives by the government in the US and Canada are contributing to the growth of the market in this region.

 

Artificial Intelligence for Histopathology Market


Segment Covered

The report on global artificial intelligence for histopathology market covers segments such as model, and end user. On the basis of model, the sub-markets include deep learning, and machine learning. On the basis of end user, the sub-markets include pharmaceutical & biotechnology companies, hospitals and reference laboratories, and academic & research institutes.

 

Companies Profiled:

The report provides profiles of the companies in the market such as ContextVision, Proscia, Koninklijke Philips N.V, Hamamatsu Photonics, Leica Biosystems, Roche, 3DHISTECH, Apollo Enterprise Imaging, Huron Digital Pathology, and Visiopharm A/S.

 

Report Highlights:

The report provides deep insights into the demand forecasts, market trends, and micro and macro indicators. In addition, this report provides insights into the factors that are driving and restraining the growth in this market. Moreover, The IGR-Growth Matrix analysis given in the report brings an insight into the investment areas that existing or new market players can consider. The report provides insights into the market using analytical tools such as Porter's five forces analysis and DRO analysis of artificial intelligence for histopathology market. Moreover, the study highlights current market trends and provides forecast from 2020-2026. We also have highlighted future trends in the market that will affect the demand during the forecast period. Moreover, the competitive analysis given in each regional market brings an insight into the market share of the leading players.


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