Ensemble learning for predicting microsatellite instability in colorectal cancer using pretreatment colonoscopy images and clinical data.

ABSTRACT:

Background

Microsatellite instability (MSI) is an important molecular biomarker in colorectal cancer (CRC), associated with favorable prognosis and response to immune checkpoint inhibitors. Conventional MSI testing, including immunohistochemistry (IHC) and polymerase chain reaction (PCR), is invasive, time-consuming, and resource-dependent, underscoring the need for non-invasive and automated alternatives. This study aimed to develop and evaluate an ensemble learning framework integrating pretreatment colonoscopy images and routine clinical data for non-invasive MSI prediction in CRC.

Methods

In this retrospective study, patients with pathologically confirmed CRC and IHC-determined MSI status were included. Pretreatment colonoscopy images and routine clinical variables were

SUBMITTER: You J 

PROVIDER: S-EPMC12807959 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature