Classification Algorithm Performance Study on Diabetes Electronic Medical Records
10.3969/j.issn.1673-6036.2018.02.015
- VernacularTitle:糖尿病电子病历分类算法性能研究
- Author:
Mei-Jie YANG
1
;
Yuan DENG
Author Information
1. 重庆医科大学医学信息学院重庆400016
- Keywords:
SQL;
Diabetes;
Electronic Medical Records (EMR);
Weka 3.9;
Naive bayesian
- From:
Journal of Medical Informatics
2018;39(2):65-68,77
- CountryChina
- Language:Chinese
-
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.
