Machine-learning-based Analysis Identifies miRNA Expression Profile for Diagnosis and Prediction of Colorectal Cancer: A Preliminary Study.

ABSTRACT:

Background

The stage of colorectal cancer (CRC) at the day of diagnosis has the greatest influence on survival rate. Thus, for CRC, which is mainly identified as advanced disease, non-invasive, molecular blood or stool tests could boost the diagnosis and lower mortality. Evaluation of miRNA expression levels in serum of patients diagnosed with CRC is a potential tool in early screening. Screening can be supported by machine learning (ML) as a tool for developing a cancer risk predictive model based on genetic data.

Materials and methods

miRNA was isolated from the serum of 8 patients diagnosed with CRC and 10 patients from a control group matched for age and sex. The expression of 179 miRNAs was determined using a serum/plasma panel (Exiqon). Determinations were conducted us

SUBMITTER: Pawelka D 

PROVIDER: S-EPMC9247881 | biostudies-literature | 2022 Jul-Aug

REPOSITORIES: biostudies-literature