Genes selection using deep learning and explainable artificial intelligence for chronic lymphocytic leukemia predicting the need and time to therapy

Analyzing gene expression profiles (GEP) through artificial intelligence provides meaningful insight into cancer disease. This study introduces DeepSHAP Autoencoder Filter for Genes Selection (DSAF-GS), a novel deep learning and explainable artificial intelligence-based approach for feature selectio...

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Bibliografiske detaljer

Principais autores:	Fortunato Morabito, Carlo Adornetto, Paola Monti, Adriana Amaro, Francesco Reggiani, Monica Colombo, Yissel Rodriguez-Aldana, Giovanni Tripepi, Graziella D’Arrigo, Claudia Vener, Federica Torricelli, Teresa Rossi, Antonino Neri, Manlio Ferrarini, Giovanna Cutrona, Massimo Gentile, Gianluigi Greco
Format:	Artigo
Sprog:	Inglês
Udgivet:	Frontiers Media S.A. 2023-08-01
Serier:	Frontiers in Oncology
Fag:	chronic lymphocytic leukemia gene expression profile deep learning explainable artificial intelligence feature selection
Online adgang:	https://www.frontiersin.org/articles/10.3389/fonc.2023.1198992/full
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