Data Mining Approach to Predict and Analyze the Cardiovascular Disease

This paper presents the experimental analysis of data provided by UCI machine learning repository. Weka open source machine learning tool provided by Waikato University reveals the hidden fact behind the datasets on applying supervised mathematical proven algorithm, i.e., J48 and Naive Bayes algorithm. J48 is an extension of ID3 algorithm having additional features like continuous attribute value ranges and derivation of rules. The data sets were analyzed using two approaches, i.e., first taken with selected attributes and taken with all attributes. The performance of both the algorithm reveals the accuracy of algorithm and predicting the various reasons behind this increasing problem of cardiovascular diseases.

[1]  G.Karthiga,et al.  Heart Disease Analysis System Using DataMining Techniques , 2014 .

[2]  Rayid Ghani,et al.  Early Prediction of Cardiac Arrest (Code Blue) using Electronic Medical Records , 2015, KDD.

[3]  M. Manimekalai,et al.  Study of Heart Disease Prediction using Data Mining , 2014 .

[4]  M. Narasimha Murty,et al.  Pattern Recognition - An Algorithmic Approach , 2011, Undergraduate Topics in Computer Science.

[5]  V. Seenivasagam,et al.  REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES , 2013, SOCO 2013.

[6]  Ritika Chadha,et al.  Prediction of heart disease using data mining techniques , 2016, CSI Transactions on ICT.

[7]  Mohammad Pooyan,et al.  Early detection of sudden cardiac death by using classical linear techniques and time-frequency methods on electrocardiogram signals , 2011 .

[8]  Beant Kaur,et al.  Review on Heart Disease Prediction System using Data Mining Techniques , 2014 .

[9]  Soni Jyoti,et al.  Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction , 2011 .

[10]  Atul Kumar Pandey,et al.  DataMining Clustering Techniques in the Prediction of Heart Disease using Attribute Selection Method , 2013 .

[11]  Sellappan Palaniappan,et al.  Intelligent heart disease prediction system using data mining techniques , 2008, 2008 IEEE/ACS International Conference on Computer Systems and Applications.

[12]  Mohammad Khubeb Siddiqui,et al.  Application of data mining: Diabetes health care in young and old patients , 2013, J. King Saud Univ. Comput. Inf. Sci..