Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture.

Joseph, Lionel P; Joseph, Erica A; Prasad, Ramendra

Joseph, Lionel P; Joseph, Erica A; Prasad, Ramendra.

Afiliação

Joseph LP; School of Mathematics, Physics, and Computing, University of Southern Queensland, Springfield, QLD, 4300, Australia.
Joseph EA; Umanand Prasad School of Medicine and Health Sciences, The University of Fiji, Saweni, Lautoka, Fiji.
Prasad R; Department of Science, School of Science and Technology, The University of Fiji, Saweni, Lautoka, Fiji. Electronic address: ramendrap@unifiji.ac.fj.

Comput Biol Med ; 151(Pt A): 106178, 2022 12.

Article em En | MEDLINE | ID: mdl-36306578

Assuntos

Diabetes Mellitus; Poliúria; Humanos; Inteligência Artificial; Teorema de Bayes; Insulina

Palavras-chave

Attention mechanism; Bayesian optimization; Diabetes classification; Interpretability; TabNet; eXplainable artificial intelligence (XAI); "Black-box" models

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Poliúria / Diabetes Mellitus Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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