Design of risk prediction model for esophageal cancer based on machine learning approach.

ABSTRACT:

Background and aim

Esophageal cancer (EC) is a highly prevalent and progressive disease. Early prediction of EC risk in the population is crucial in preventing this disease and enhancing the overall health of individuals. So far, few studies have been conducted on predicting the EC risk based on the prediction models, and most of them focused on statistical methods. The ML approach obtained efficient predictive insights into the clinical domain. Therefore, this study aims to develop a risk prediction model for EC based on risk factors and by leveraging the ML approach to stratify the high-risk EC people and obtain efficient preventive purposes at the community level.

Material and methods

The current retrospective study was performed from 2018 to 2022 in Sari City based on 32

SUBMITTER: Nopour R 

PROVIDER: S-EPMC10835323 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature