Visualizing Decisions and Analytics of Artificial Intelligence based Cancer Diagnosis and Grading of Specimen Digitized Biopsy: Case Study for Prostate Cancer
Amal, S.; Singh, A.; Harrison, L.; Breggia, A.; Christman, R.; Winslow, R. L.; Wan, M.
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1The rise in Artificial Intelligence (AI) and deep learning research has shown great promise in diagnosing prostate cancer from whole slide image biopsies. Intelligent application interface for diagnosis is a progressive way to communicate AI results in the medical domain for practical use. This paper aims to suggest a way to integrate state-of-the-art deep learning algorithms into a web application for visualizations of decisions and analytics of an AI based algorithms applied on cancer digitized specimen biopsies together with visualizing evidence and explanation of the decision using both image from the biopsy and textual data from Electronic Health Records (EHR). By creating smart visualizations of tissue biopsy images, from magnified regions to augmented sharper images along with image masks that highlight cancerous regions of tissue in addition to intelligent analytics and distribution charts related to cancer prediction, we aim to communicate these easily interpretable results to assist pathologists and concerned medical team to make better decisions for prostate cancer diagnosis as case study.
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