TopOC: Topological Deep Learning for Ovarian and Breast Cancer Diagnosis

Saba Fatema, Brighton Nuwagira, Sayoni Chakraborty, Reyhan Gedik, Baris Coskunuzer

Abstract: Microscopic examination of slides prepared from tissue samples is the primary tool for detecting and classifying cancerous lesions, a process that is time-consuming and requires the expertise of experienced pathologists. Recent advances in deep learning methods hold significant potential to enhance medical diagnostics and treatment planning by improving accuracy, reproducibility, and speed, thereby reducing clinicians’ workloads and turnaround times. However, the necessity for vast amounts of labeled data to train these models remains a major obstacle to the development of effective clinical decision support systems.