Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer.

ABSTRACT:

Purpose

Machine learning (ML) is a strong candidate for making accurate predictions, as we can use large amount of data with powerful computational algorithms. We developed a ML based model to predict survival of patients with colorectal cancer (CRC) using data from two independent datasets.

Materials and methods

A total of 364,316 and 1,572 CRC patients were included from the Surveillance, Epidemiology, and End Results (SEER) and a Korean dataset, respectively. As SEER combines data from 18 cancer registries, internal validation was done using 18-Fold-Cross-Validation then external validation was performed by testing the trained model on the Korean dataset. Performance was evaluated using area under the receiver operating characteristic curve (AUROC), sensitivity and positi

SUBMITTER: Osman MH 

PROVIDER: S-EPMC9016295 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature