Machine Learning-Based Algorithms for Enhanced Prediction of Local Recurrence and Metastasis in Low Rectal Adenocarcinoma Using Imaging, Surgical, and Pathological Data

Machine Learning-Based Algorithms for Enhanced Prediction of Local Recurrence and Metastasis in Low Rectal Adenocarcinoma Using Imaging, Surgical, and Pathological Data

(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 pre...

Full description

Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Diagnostics
Subjects:
rectal cancer
machine learning
risk factors
metastasis
recurrence
Online Access:https://www.mdpi.com/2075-4418/14/6/625

Internet

https://www.mdpi.com/2075-4418/14/6/625

Similar Items