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Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome.

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Title: Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome.
Authors: Pons-Suñer, Pedro1 (AUTHOR) pedropons@iti.es, Signol, François1 (AUTHOR) fsignol@iti.es, Alvarez, Noemi2 (AUTHOR) noalva01@ucm.es, Sargas, Claudia3 (AUTHOR) claudia_sargas@iislafe.es, Dorado, Sara4 (AUTHOR) sara_dorado@altumsequencing.com, Ortí, Jose Vicente Gil3 (AUTHOR) jose_gil@iislafe.es, Delgado Sanchis, Juan A.1 (AUTHOR) jadelgado@iti.es, Llop, Marta3 (AUTHOR) llop_margar@gva.es, Arnal, Laura1 (AUTHOR) larnal@iti.es, Llobet, Rafael1 (AUTHOR) rllobet@iti.es, Perez-Cortes, Juan-Carlos1 (AUTHOR) jcperez@iti.es, Ayala, Rosa2 (AUTHOR) rosam.ayala@salud.madrid.org, Barragán, Eva3 (AUTHOR) barragan_eva@gva.es
Source: BMC Medical Informatics & Decision Making. 5/1/2025, Vol. 25 Issue 1, p1-22. 22p.
Database: Academic Search Ultimate
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Description
ISSN:14726947
DOI:10.1186/s12911-025-03001-y