An oral microbiota-based deep neural network model for risk stratification and prognosis prediction in gastric cancer.

ABSTRACT:

Background

This study aims to develop an oral microbiota-based model for gastric cancer (GC) risk stratification and prognosis prediction.

Methods

Oral microbial markers for GC prognosis and risk stratification were identified from 99 GC patients, and their predictive potential was validated on an external dataset of 111 GC patients. The identified bacterial markers were used to construct a Deep Neural Network (DNN) model, a Random Forest (RF) model, and a Support Vector Machine (SVM) model for predicting GC prognosis.

Results

GC patients with <3 years of survival showed a higher abundance of Aggregatibacter and diminished abundances of Filifactor and Moryella than those who survived ≥3 years. The Boruta algorithm unearthed Leptotrichia as another signif

SUBMITTER: Gao XF 

PROVIDER: S-EPMC11749243 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature