Developing a Software for Diagnosing Heart Disease via Data Mining Techniques

• Main Authors: Yaser AbdulAali JASIM, Mustafa G. SAEED
• Format: Article
• Language: English
• Published: Ediciones Universidad de Salamanca 2018-12-01
• Series: Advances in Distributed Computing and Artificial Intelligence Journal
• Subjects: data mining, artificial neural network, matlab r2016a and heart disease
• Online Access: https://revistas.usal.es/index.php/2255-2863/article/view/18964

<p>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.</p>