Deep Learning Features Can Improve Radiomics-Based Prostate Cancer Aggressiveness Prediction out on @JCO_ASCO Clinical Cancer Informatics ascopubs.org/doi/abs/10.1200… Study explores how artificial intelligence🖥️, particularly deep learning models, can enhance the detection and treatment of #ProstateCancer by improving radiomic signature models used for disease aggressiveness classification. Traditionally, radiomics involves independent segmentation and feature extraction, but this research suggests that prostate segmentation and reconstruction models offer additional valuable information. The study, which involved 2,244 experiments using deep learning features from 13 models, shows that combining deep features with radiomic data often enhances predictive performance. However, the choice of feature selection methods, such as PCA, plays a critical role in determining success. @npap69