文章基本信息

标题：An Algorithm for Predictive Data Mining Approach in Medical Diagnosis
作者：Shakuntala Jatav ; Vivek Sharmam
期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2018
卷号：10
期号：1
页码：11-20
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The Healthcare industry contains big and complex data that may be required in order to discoverfascinating pattern of diseases & makes effective decisions with the help of different machine learningtechniques. Advanced data mining techniques are used to discover knowledge in database and for medicalresearch. This paper has analyzed prediction systems for Diabetes, Kidney and Liver disease using morenumber of input attributes. The data mining classification techniques, namely Support VectorMachine(SVM) and Random Forest (RF) are analyzed on Diabetes, Kidney and Liver disease database.The performance of these techniques is compared, based on precision, recall, accuracy, f_measure as wellas time. As a result of study the proposed algorithm is designed using SVM and RF algorithm and theexperimental result shows the accuracy of 99.35%, 99.37 and 99.14 on diabetes, kidney and liver diseaserespectively.
关键词：Data Mining; Clinical Decision Support System; Disease Prediction; Classification; SVM; RF.