Clinical Evaluation of Prostate Cancer using Machine Learning-Based Pathology Report Generation

A machine learning-based framework for summarizing prostate cancer and related findings through a pathology report generator. This report generator reduces time-consuming annotations and tumor volume estimation during clinical routines by extracting and summarizing relevant information into a pathology report to aid pathologist workflow. The framework can also determine subsets with increased risk for genomic alterations, high-risk of biochemical recurrence, and cancer-specific survival from a set of histology images.

Stage of Research