Bioinformatics In Urology — Molecular Characterization Of Pathophysiology And Response To Treatment

This article discusses the development and implementation of computational approaches, such as ML algorithms, and their application to discrete aspects of urology in clinical practice and research. It focuses on the use of bioinformatics for genitourinary cancers, including the identification of molecular subtypes, prognostic and predictive biomarkers, and mechanisms of tumour evolution. It also covers computational approaches to functional urological disorders, and best practices in the use of bioinformatics and ML applications in urology.