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Classification Algorithm Performance Study on Diabetes Electronic Medical Records / 医学信息学杂志
Journal of Medical Informatics ; (12): 65-68,77, 2018.
Artículo en Chino | WPRIM | ID: wpr-700756
ABSTRACT
The paper preprocesses the data including basic information,admission and discharge record and progress note of diabetes Electronic Medical Records (EMR),implementing decision tree,Artificial Neural Network (ANN),Naive bayesian and K-Nearest Neighbor (KNN) classifications respectively on data that have been processed with Weka 3.9.The result shows that Naive bayesian classification,which is superior to the others in predicting and classifying such data,can provide basis for the classification and prediction of diabetes.

Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Tipo de estudio: Estudio pronóstico Idioma: Chino Revista: Journal of Medical Informatics Año: 2018 Tipo del documento: Artículo

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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Tipo de estudio: Estudio pronóstico Idioma: Chino Revista: Journal of Medical Informatics Año: 2018 Tipo del documento: Artículo