1. Pathomics in urology
- Author
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Victor M. Schuettfort, Michael Rink, Eva Compérat, Benjamin Pradere, and Shahrokh F. Shariat
- Subjects
medicine.medical_specialty ,business.industry ,Urology ,030232 urology & nephrology ,MEDLINE ,Disease classification ,Cancer ,medicine.disease ,03 medical and health sciences ,Prostate cancer ,0302 clinical medicine ,030220 oncology & carcinogenesis ,medicine ,Generalizability theory ,Gleason scores ,business - Abstract
Purpose of review Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summarize its most relevant applications in urology. Recent findings There is a steady rise in the number of studies employing Pathomics, and especially deep learning, in urology. In prostate cancer, several algorithms have been developed for the automatic differentiation between benign and malignant lesions and to differentiate Gleason scores. Furthermore, several applications have been developed for the automatic cancer cell detection in urine and for tumor assessment in renal cancer. Despite the explosion in research, Pathomics is not fully ready yet for widespread clinical application. Summary In prostate cancer and other urologic pathologies, Pathomics is avidly being researched with commercial applications on the close horizon. Pathomics is set to improve the accuracy, speed, reliability, cost-effectiveness and generalizability of pathology, especially in uro-oncology.
- Published
- 2020