Cristian-Constantin Volovat, Dragos-Viorel Scripcariu, Diana Boboc, Simona-Ruxandra Volovat, Ingrid-Andrada Vasilache, Corina Ursulescu-Lupascu, Liliana Gheorghe, Luiza-Maria Baean, Constantin Volovat, Viorel Scripcariu
(1) Background: Numerous variables could influence the risk of rectal cancer recurrence or metastasis, and machine learning (ML)-based algorithms can help us refine the risk stratification process of these patients and choose the best therapeutic approach. The aim of this study was to assess the predictive performance of 4 ML-based models for the prediction of local recurrence or distant metastasis in patients with locally advanced low rectal adenocarcinomas who underwent neoadjuvant chemoradiotherapy and surgical treatment; (2) Methods: Patients who were admitted at the first Oncologic Surgical Clinic from the Regional Institute of Oncology, Iasi, Romania were retrospectively included in this study between November 2019 and July 2023...
March 15, 2024: Diagnostics