UC5: Dataset for Recurrence Risk Prediction After Radical Prostatectomy

The UC5: Dataset for Recurrence Risk Prediction After Radical Prostatectomy comprises detailed clinical, imaging, and pathological information from patients who have undergone radical prostatectomy. The dataset includes both cases with and without biochemical relapse and features post-operative findings such as positive surgical margins and extracapsular extension. Additionally, it integrates imaging-derived radiomic features and relevant clinical variables, forming a rich resource for training and validating artificial intelligence models aimed at recurrence risk stratification. The primary objective of the dataset is to enable the creation of predictive tools, including AI-powered nomograms, that forecast the likelihood of disease recurrence following prostate surgery. By leveraging comprehensive patient data, the dataset supports the advancement of precision medicine approaches in urologic oncology. This enables more informed decision-making regarding surgical techniques—ranging from conventional open to minimally invasive or nerve-sparing procedures—tailored to the individual risk profile of each patient.