Text mining-based identification of promising miRNA biomarkers for diabetes mellitus.

ABSTRACT:

Introduction

MicroRNAs (miRNAs) are small, non-coding RNAs that play a critical role in diabetes development. While individual studies investigating the mechanisms of miRNA in diabetes provide valuable insights, their narrow focus limits their ability to provide a comprehensive understanding of miRNAs' role in diabetes pathogenesis and complications.

Methods

To reduce potential bias from individual studies, we employed a text mining-based approach to identify the role of miRNAs in diabetes and their potential as biomarker candidates. Abstracts of publications were tokenized, and biomedical terms were extracted for topic modeling. Four machine learning algorithms, including Naïve Bayes, Decision Tree, Random Forest, and Support Vector Machines (SVM), were employed for diabete

SUBMITTER: Li X 

PROVIDER: S-EPMC10407569 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature