EXPLAINABLE MACHINE LEARNING FOR NON-INVASIVE PROSTATE CANCER DETECTION USING SIGNAL-DERIVED VOC FEATURES
The present study aimed to develop an explainable artificial intelligence (AI) model by using urinary volatile organic compound (VOC) profiles for non-invasive prostate cancer (PCa) detection. A total of 123 participants were included: 29 with PCa, 67 with benign prostatic hyperplasia (BPH), and 27 healthy controls. Ur...