%0 Journal Article
%T Developing a Software for Diagnosing Heart Disease via Data Mining Techniques
%A Mustafa G. SAEED
%A Yaser AbdulAali JASIM
%J -
%D 2018
%R http://dx.doi.org/10.14201/ADCAIJ20187399114
%X This paper builds a data mining tool via a classification method using Multi-Layer Perceptron (MLP) with Backpropagation learning method and an algorithm of feature selection along with biomedical testing values for diagnosing heart disease. Addition to that, developing a prototype for heart disease diagnosing with a friendly-user graphical interface (GUI). The purpose to construct this software is that; clinical prosopopoeia is done in any event by doctor¡¯s experience. Despite that, some cases are reported negative diagnosis and treatment; therefore, patients are asked to take a number of tests for diagnosis. Moreover, not all the tests contribute towards an effective diagnosis of a disease, and by using data mining approach to diagnose heart disease that supports the doctors to make more efficient and subtle decisions
%K Data mining
%K Artificial Neural Network
%K Matlab R2016a and Heart disease
%U http://campus.usal.es/~revistas_trabajo/index.php/2255-2863/article/view/ADCAIJ20187399114