Prediction of heart disease using multilayer perceptron neural network

In medical field the diagnosis of heart disease is most difficult task. It depends on the careful analysis of different clinical and pathological data of the patient by medical experts, which is complicated process. Due to advancement in machine learning and information technology, the researchers and medical practitioners in large extent are interested in the development of automated system for the prediction of heart disease that is highly accurate, effective and helpful in early diagnosis. In this paper we present a prediction system for heart disease using multilayer perceptron neural network. The neural network in this system accepts 13 clinical features as input and it is trained using back-propagation algorithm to predict that there is a presence or absence of heart disease in the patient with highest accuracy of 98% comparative to other systems. The accuracy thus obtained with this system shows that it is better and efficient than other systems.

[1]  Cheng-Lung Huang,et al.  A GA-based feature selection and parameters optimizationfor support vector machines , 2006, Expert Syst. Appl..

[2]  M Anbarasi,et al.  ENHANCED PREDICTION OF HEART DISEASE WITH FEATURE SUBSET SELECTION USING GENETIC ALGORITHM , 2010 .

[3]  Du-Yih Tsai,et al.  A method for optimization of fuzzy reasoning by genetic algorithms and its application to discrimination of myocardial heart disease , 1998, 1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255).

[4]  Alan V. Sahakian,et al.  Automated Recognition of Obstructive Sleep Apnea Syndrome Using Support Vector Machine Classifier , 2012, IEEE Transactions on Information Technology in Biomedicine.

[5]  Prabhat Panday,et al.  Decision Support System for Cardiovascular Heart Disease Diagnosis using Improved Multilayer Perceptron , 2012 .

[6]  A. Rajkumar,et al.  Diagnosis Of Heart Disease Using Datamining Algorithm , 2010 .

[7]  W. Baxt.  Application of artificial neural networks to clinical medicine , 1995, The Lancet.

[8]  Zainal Abidin,et al.  Utilization of an artificial neural network in the prediction of heart disease , 2013 .

[9]  Asha Rajkumar,et al.  Diagonsis of Heaer Disease using Datamining Algorithm , 2010 .

[10]  Imad H. Elhajj,et al.  Support Vector Machines to Define and Detect Agitation Transition , 2010, IEEE Transactions on Affective Computing.

[11]  Kapil Wankhade,et al.  Decision support system for heart disease based on support vector machine and Artificial Neural Network , 2010, 2010 International Conference on Computer and Communication Technology (ICCCT).

[12]  N. Nithiyanandam,et al.  Automatic diagnosis of heart diseases using neural network , 1996, Proceedings of the 1996 Fifteenth Southern Biomedical Engineering Conference.

[13]  Chetan Patil,et al.  Heart Disease Diagnosis using Support Vector Machine , 2011 .

[14]  S. N. Sivanandam,et al.  Principles of soft computing , 2011 .

[15]  Shrinivas D. Desai,et al.  Intelligent Heart Disease Prediction System Using Probabilistic Neural Network , 2013 .