Blood Uric Acid Prediction With Machine Learning: Model Development and Performance Comparison.

Sampa, Masuda Begum; Hossain, Md Nazmul; Hoque, Md Rakibul; Islam, Rafiqul; Yokota, Fumihiko; Nishikitani, Mariko; Ahmed, Ashir

Sampa, Masuda Begum; Hossain, Md Nazmul; Hoque, Md Rakibul; Islam, Rafiqul; Yokota, Fumihiko; Nishikitani, Mariko; Ahmed, Ashir.

Afiliação

Sampa MB; Department of Advanced Information Technology, Kyushu University, Fukuoka, Japan.
Hossain MN; Department of Marketing, Faculty of Business Studies, University of Dhaka, Dhaka, Bangladesh.
Hoque MR; School of Business, Emporia State University, Kansas, KS, United States.
Islam R; Medical Information Center, Kyushu University Hospital, Fukuoka, Japan.
Yokota F; Institute of Decision Science for a Sustainable Society, Kyushu University, Fukuoka, Japan.
Nishikitani M; Medical Information Center, Kyushu University Hospital, Fukuoka, Japan.
Ahmed A; Department of Advanced Information Technology, Kyushu University, Fukuoka, Japan.

JMIR Med Inform ; 8(10): e18331, 2020 Oct 08.

Article em En | MEDLINE | ID: mdl-33030442

Palavras-chave

Bangladesh; blood uric acid; boosted decision tree regression model; machine learning; noncommunicable diseases; urban corporate population

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: JMIR Med Inform Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Japão

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