Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …

Advances in our understanding of the role of magnetic resonance imaging (MRI) for the
detection of prostate cancer have enabled its integration into clinical routines in the past two …

Radiomics and genomics represent two of the most promising fields of cancer research,
designed to improve the risk stratification and disease management of patients with prostate …

The application of radiogenomics in oncology has great prospects in precision medicine.
Radiogenomics combines large volumes of radiomic features from medical digital images …

The present study aimed to explore the potential of artificial intelligence (AI) methodology
based on magnetic resonance (MR) images to aid in the management of prostate cancer …

Simple Summary Existing research on predicting biochemical recurrence after prostate
surgery has been insufficient. Here, we aimed to predict biochemical recurrence after radical …

Objectives This study aims to develop and evaluate multiparametric MRI (MP-MRI)-based
radiomic models as a noninvasive diagnostic method to predict several biological …

Although prostate cancer is one of the most common causes of mortality and morbidity in
advancing-age males, early diagnosis improves prognosis and modifies the therapy of …

Purpose To evaluate if machine learning (ML) of radiomic features extracted from apparent
diffusion coefficient (ADC) and T2-weighted (T2W) MRI can predict prostate cancer (PCa) …

Purpose To investigate the potential value of MRI radiomics obtained from a 1.5 T MRI‐
guided linear accelerator (MR‐LINAC) for D'Amico high‐risk prostate cancer (PC) …