Diabetes Detection Models in Mexican Patients by Combining Machine Learning Algorithms and Feature Selection Techniques for Clinical and Paraclinical Attributes: A Comparative Evaluation.

García-Domínguez, Antonio; Galván-Tejada, Carlos E; Magallanes-Quintanar, Rafael; Gamboa-Rosales, Hamurabi; Curiel, Irma González; Peralta-Romero, Jesús; Cruz, Miguel

García-Domínguez, Antonio; Galván-Tejada, Carlos E; Magallanes-Quintanar, Rafael; Gamboa-Rosales, Hamurabi; Curiel, Irma González; Peralta-Romero, Jesús; Cruz, Miguel.

Afiliação

García-Domínguez A; Academic Unit of Electrical Engineering, Autonomous University of Zacatecas, Juárez Garden 147, Downtown, Zacatecas 98000, Mexico.
Galván-Tejada CE; Academic Unit of Electrical Engineering, Autonomous University of Zacatecas, Juárez Garden 147, Downtown, Zacatecas 98000, Mexico.
Magallanes-Quintanar R; Academic Unit of Electrical Engineering, Autonomous University of Zacatecas, Juárez Garden 147, Downtown, Zacatecas 98000, Mexico.
Gamboa-Rosales H; Academic Unit of Electrical Engineering, Autonomous University of Zacatecas, Juárez Garden 147, Downtown, Zacatecas 98000, Mexico.
Curiel IG; Academic Unit of Chemical Sciences, Autonomous University of Zacatecas, Juarez Garden 147, Downtown, Zacatecas 98000, Mexico.
Peralta-Romero J; Medical Research Unit in Biochemistry, Specialties Hospital, National Medical Center Siglo XXI, Mexican Social Security Institute, Mexico City, Mexico.
Cruz M; Medical Research Unit in Biochemistry, Specialties Hospital, National Medical Center Siglo XXI, Mexican Social Security Institute, Mexico City, Mexico.

J Diabetes Res ; 2023: 9713905, 2023.

Article em En | MEDLINE | ID: mdl-37404324

Assuntos

Algoritmos; Diabetes Mellitus; Humanos; Teorema de Bayes; Aprendizado de Máquina; Diabetes Mellitus/diagnóstico; Algoritmo Florestas Aleatórias

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Diabetes Mellitus Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans País/Região como assunto: Mexico Idioma: En Revista: J Diabetes Res Ano de publicação: 2023 Tipo de documento: Article País de afiliação: México

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