A Microenvironment-Aware Deep Learning Framework Leveraging Gland-Stroma Morphological Signatures for Prostate Cancer Prognostic Risk Stratification
Ph.D. Research Symposium Talk, Luddy School of Informatics, Computing, and Engineering, Indiana University Indianapolis, Indianapolis, IN, USA
Presented at the Luddy Ph.D. Research Symposium at Indiana University Indianapolis. This presentation introduced a microenvironment-aware deep learning framework that leverages gland-stroma morphological signatures for prostate cancer prognostic risk stratification. The talk highlighted the integration of computational pathology and deep learning techniques to improve prognostic assessment and support precision oncology research.