Early Detection of Heart Syndrome Using Machine Learning Technique

被引:0
作者
Basha, Noor [1 ]
Kumar, Ashok P. S. [2 ]
Krishna, Gopal C. [3 ]
Venkatesh, P. [4 ]
机构
[1] Vemana Inst Technol, Dept CSE, Bengaluru, India
[2] Don Bosco Inst Technol, Dept CSE, Bengaluru, India
[3] Adi Chunchanagiri Inst Technol, Dept CSE, Chikmagaluru, India
[4] Don Bosco Inst Technol, Dept TCE, Bengaluru, India
来源
2019 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, COMMUNICATION, COMPUTER TECHNOLOGIES AND OPTIMIZATION TECHNIQUES (ICEECCOT) | 2019年
关键词
Heart Disease; KNN; Decision Tree; Random Forest; SVM; Naive Bayes;
D O I
10.1109/iceeccot46775.2019.9114651
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Analysis and Prediction of diseases are two most demanding factors to be faced critically by the doctors and data scientist, where data analytics be very delightful issue, so in this regard, many health industries will working on variety of human syndromes, where they generate huge data. Heart disease, cancer, tumour and Alzheimer's disease are one of the chronic human diseases, where data scientist and doctors are doing rapid and efficient analysis on these diseases using many machine learning techniques to study and predict these diseases to save and reduce human deaths. Importance of this article is to predict and analyze the heart related syndrome in patients, based on one of the main feature, like age, where data scientists can do predictive research on big data to early analysis on heart syndrome to save the life of the patients. In this case study many features are well thought-out to do AN analysis and predict of heart diseases in patients, here author checked with prediction of data using many machine learning algorithm are used to verify the performance of syndrome
引用
收藏
页码:387 / +
页数:5
相关论文
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