Artificial Intelligence and Complex Network Approaches Reveal Potential Gene Biomarkers for Hepatocellular Carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and the number of cases is constantly increasing. Early and accurate HCC diagnosis is crucial to improving the effectiveness of treatment. The aim of the study is to develop a supervised learning framework based on hierarchical community detection and artificial intelligence in order to classify patients and controls using publicly available microarray data. With our methodology, we identified 20 gene communities that discriminated between healthy and cancerous samples, with an accuracy exceeding 90%. We validated the performance of these communities on an independent dataset, and with two of them, we reached an accuracy exceeding 80%. Then, we focused on two communities, selected because they were enriched with re

SUBMITTER: Lacalamita A 

PROVIDER: S-EPMC10607580 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature