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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.
Article in Chinese | WPRIM (Western Pacific) | ID: wpr-700756
Responsible library: WPRO
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.

Full text: Available Health context: Sustainable Health Agenda for the Americas Health problem: Goal 6: Information systems for health Database: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Journal of Medical Informatics Year: 2018 Document type: Article
Full text: Available Health context: Sustainable Health Agenda for the Americas Health problem: Goal 6: Information systems for health Database: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Journal of Medical Informatics Year: 2018 Document type: Article
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