Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.

ABSTRACT: Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by grouping patients according to clinical characteristics. Based on neural network techniques, our objective was to identify those factors for HIV/HCV co-infected patients (to which clinicians have given careful consideration before treatment uptake) that have not being included among the prioritisation criteria. This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. An evolutionar

SUBMITTER: Rivero-Juarez A 

PROVIDER: S-EPMC6953863 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature