Maheswari Subburaj, Pitchai Ramu
Department of Computer Science and Engineering, National Engineering College, Kovilpatti-628503, Tamil nadu, India.
Department of Computer Science and Engineering, B.V. Raju Institute of Technology, Vishnupur, Narsapur, Telangana 502313, India.
Curr Med Imaging Rev. 2019;15(8):712-717. doi: 10.2174/1573405614666180322141259.
The huge information of healthcare data is collected from the healthcare industry which is not "mined" unfortunately to make effective decision making for the identification of hidden information. The end user support system is used as the prediction application for the heart disease and this paper proposes windows through the intelligent prediction system the instance guidance for the heart disease is given to the user. Various symptoms of the heart diseases are fed into the application. The user precedes the processes by checking the specific detail and symptoms of the heart disease. The decision tree (ID3) and navie Bayes techniques in data mining are used to retrieve the details associated with each patient. Based on the accurate result prediction, the performance of the system is analyzed.
医疗保健数据的海量信息是从医疗行业收集而来的，但遗憾的是，这些数据并未被“挖掘”以用于做出有效的决策，从而识别隐藏信息。终端用户支持系统被用作心脏病的预测应用程序，本文通过智能预测系统提出了窗口，为用户提供了心脏病的实例指导。各种心脏病症状被输入到应用程序中。用户通过检查心脏病的具体细节和症状来进行相关流程。数据挖掘中的决策树（ID3）和朴素贝叶斯技术被用于检索与每个患者相关的详细信息。基于准确的结果预测，对系统的性能进行了分析。
