Heart Disease Diagnosis System based on Multi-Layer Perceptron neural network and Support Vector Machine

The area of medical information has advanced around organizing, preparing, storing, and transmit medical data for an assortment of purposes. One of these intentions is to create choice emotionally supportive networks that upgrade the human ability to analyze, treat, and evaluate forecasts of pathologic conditions. In this paper, heart disease diagnosis system has been built to classify two cases of heart conditions (Normal, Abnormal) in additional to classify five cases namely (Coronary Heart Disease, Angina Pectoris, Congestive Heart Failure, Arrhythmias, And Normal case), with high probability of classification. The proposed Heart disease diagnostic system consists of two types of database are used in the classification process; The online database which is taking from UCI learning data set repository for diagnosis heart disease and collected database from Ibn Al-Bitar Hospital Cardia Surgery and Baghdad Medical City. These databases consist of thirteen medical factors that are successful to diagnosis heart disease. Two heart diseases classifiers are proposed. They are; Multi-Layer Perceptron neural network (MLP), and Support Vector Machin (SVM). The simulation results show that, the MLP classifier has 98% accuracy of two heart diseases classification when the performance of this classifier was evaluated using collected database. While the accuracy of SVM classifier is reached 96%. Also, MLP has overcome from SVM classifier when classify four type of heart disease in additional to normal case for accuracy reached to 81%.

[1]  Abhishek Singh Rathore,et al.  Heart Disease Diagnosis , 2019, Advances in Medical Technologies and Clinical Practice.

[2]  Semih Ergin,et al.  A new feature extraction framework based on wavelets for breast cancer diagnosis , 2014, Comput. Biol. Medicine.

[3]  Yingtao Jiang,et al.  A multilayer perceptron-based medical decision support system for heart disease diagnosis , 2006, Expert Syst. Appl..

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

[5]  K. Gunavathi,et al.  Lung cancer classification using fuzzy logic for CT images , 2015, Int. J. Medical Eng. Informatics.

[6]  Oyebade K. Oyedotun,et al.  Heart Diseases Diagnosis Using Neural Networks Arbitration , 2015 .

[7]  Sheetal Sonawane,et al.  Classification Of Heart Disease Using SVM And ANN , 2013 .

[8]  Jan Juretzka,et al.  Decision Support System , 2001 .

[9]  Chih-Jen Lin,et al.  A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.

[10]  G. Pillai,et al.  SVM Based Decision Support System for Heart Disease Classification with Integer-Coded Genetic Algorithm to Select Critical Features , 2009 .

[11]  K. Gunavathi,et al.  Lung cancer classification using neural networks for CT images , 2014, Comput. Methods Programs Biomed..

[12]  OzturkCelal,et al.  A comprehensive survey , 2014 .

[13]  Ataollah Ebrahimzadeh,et al.  Automatic Recognition of Digital Communication Signal , 2012 .

[14]  Shashikant Ghumbre,et al.  Heart Disease Diagnosis Using Machine Learning Algorithm , 2012 .

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

[16]  Lorenzo Bruzzone,et al.  Classification of hyperspectral remote sensing images with support vector machines , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Qian Wang,et al.  A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method , 2017, Comput. Math. Methods Medicine.

[18]  Omar Adwan,et al.  Automatic Heart Disease Diagnosis System Based on Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) Approaches , 2014 .

[19]  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).

[20]  Himansu Sekhar Behera,et al.  A Comprehensive Survey on Support Vector Machine in Data Mining Tasks: Applications & Challenges , 2015 .

[21]  Veera Boonjing,et al.  Heart Disease Classification Using Neural Network and Feature Selection , 2011, 2011 21st International Conference on Systems Engineering.

[22]  Usman Qamar,et al.  An ensemble based decision support framework for intelligent heart disease diagnosis , 2014, International Conference on Information Society (i-Society 2014).

[23]  Majid Ghonji Feshki,et al.  Improving the heart disease diagnosis by evolutionary algorithm of PSO and Feed Forward Neural Network , 2016, 2016 Artificial Intelligence and Robotics (IRANOPEN).

[24]  Sheetal Sonawane,et al.  DECISION SUPPORT SYSTEM FOR HEART DISEASE BASED ON SEQUENTIAL MINIMAL OPTIMIZATION IN SUPPORT VECTOR MACHINE , 2013 .

[25]  Dharmaraj R. Patil,et al.  Survey on Decision Support System For Heart Disease , 2013 .

[26]  D. Culler,et al.  Comparison of methods , 2000 .

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