Machine Learning-Based Morphologic Characterization of Genitourinary Malignancies
Abstract: In recent years, the field of medicine has witnessed a remarkable transformation with the advent of cutting-edge computer-based image and pattern analyses. These approaches have proven exceptionally adept at efficiently detecting and classifying objects, including the identification of cancer from large and complex medical images. This is particularly invaluable, as such tasks can be exceedingly time-consuming for healthcare professionals. Moreover, the remarkable power of these methods lies in their capacity to delineate patterns that were previously not recognized by physicians and researchers. In this seminar, I will share our efforts in harnessing machine learning-based approaches to define morphologic features of advanced metastatic prostate cancer and bladder cancer from standard pathology images, with a focus on developing biomarkers that can guide clinical decision making.