Machine learning-based colorectal cancer prediction using global dietary data.

ABSTRACT:

Background

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Active health screening for CRC yielded detection of an increasingly younger adults. However, current machine learning algorithms that are trained using older adults and smaller datasets, may not perform well in practice for large populations.

Aim

To evaluate machine learning algorithms using large datasets accounting for both younger and older adults from multiple regions and diverse sociodemographics.

Methods

A large dataset including 109,343 participants in a dietary-based colorectal cancer ase study from Canada, India, Italy, South Korea, Mexico, Sweden, and the United States was collected by the Center for Disease Control and Prevention. This global dietary database was augm

SUBMITTER: Abdul Rahman H 

PROVIDER: S-EPMC9921106 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature