Computer Aided Diagnosis in Pathology: Pros and Cons

 

Computer-Aided-Diagnosis-in-Pathology-2Artificial Intelligence (AI) is becoming a reality in medicine. However, can these deep learning tools perform the complex tasks of Pathologists, and in some instances with superior accuracy? Image analysis is one of the main reasons pathology labs are thinking about investing in digital pathology, especially since precision medicine currently demands precision diagnostics.

Enough evidence has been accrued showing that image analysis offers better accuracy, standardization, automation, and enables computational pathology. However, there are still several drawbacks and barriers preventing widespread adoption such as limited interoperability, workflow disruption, poor reimbursement, no guidelines, and regulatory obstacles.

Dr. Liron Pantanowitz,University of Pittsburgh, USA  discussed the benefits and problems relating to computer aided diagnosis in pathology and emphasized what is required to develop those awaited killer apps during his talk at the Pathology Horizons 2017 Conference in Cairns.

View Dr. Pantanowitz’s presentation below.

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