文章基本信息

标题：Prediction of Diabetes Risk Factor Using Back Propagation and C 4.5 Algorithm
本地全文：下载
作者：Aparna Phalak ; Priti Sharma
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：6
页码：12453
DOI：10.15680/IJIRCCE.2017.0506190
出版社：S&S Publications
摘要：Prediction of diabetes is the most essential factor in Hospitalization. It is the proper way to predict morethan 500 people diabetes at a time. Due to improper prediction of diabetes it may affect to socialization andlocalization, because in news or newspaper diabetes prediction rate news arrive and this prediction rate is calculated byusing simple paper work so the lots of time takes to calculate the diabetes prediction rate so the focus of healthcarefrom reactive and hospital based to more proactive and patient-based. Electronic medical records contain patientdemographics, progress notes, problems, and medications, vital signs, past medical history, immunizations, laboratorydata and radiology report to our diabetes prediction system. There is a framework that predict the diabetes and enablesthe representation, extraction, and mining of high order latent event structure and relationships within single andmultiple event sequences by mapping the heterogeneous event sequences to a geometric image by encoding events as aBar graphs or bar charts. For creating diabetes prediction system two algorithms are used for prediction which are Backpropagation and C 4.5 algorithms. These algorithms help to predict the diabetes and save time and complicated workand give the perfect solution for predicting more than 500 people diabetes.
关键词：Temporal signature mining; sparse coding; SVM; Logistic Regression; Back propagation algorithm; C;4.5 Algorithm