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A machine learning approach for type 2 diabetes diagnosis and prognosis using tailored heterogeneous feature subsets.

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Bibliographic Details
Title: A machine learning approach for type 2 diabetes diagnosis and prognosis using tailored heterogeneous feature subsets.
Authors: Navarro-Cerdán, J. Ramón1,2, jonacer@upv.es, Pons-Suñer, Pedro3, Arnal, Laura3, Arlandis, Joaquim1,2, Llobet, Rafael1,2, Perez-Cortes, Juan-Carlos1,2, Lara-Hernández, Francisco4, Moya-Valera, Celeste4, Quiroz-Rodriguez, Maria Elena4, Rojo-Martinez, Gemma5,6, Valdés, Sergio5,6, Montanya, Eduard5,7,8, Calle-Pascual, Alfonso L.9,10, Franch-Nadal, Josep5,11, Delgado, Elias12,13, Castaño, Luis5,13,14, García-García, Ana-Bárbara4,5, Chaves, Felipe Javier4,5
Source: Medical & Biological Engineering & Computing; Sep2025, Vol. 63 Issue 9, p2733-2752, 20p
Database: Applied Science & Technology Source
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ISSN:01400118
DOI:10.1007/s11517-025-03355-5