Developing a Software for Diagnosing Heart Disease via Data Mining Techniques

• JASIM, Yaser AbdulAali ^[1] ; SAEED, Mustafa G. ^[1]
  1. [1] Cihan University

     Cihan University

     Irak

     
• Localización: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, ISSN-e 2255-2863, Vol. 7, Nº. 3, 2018, págs. 99-114
• Idioma: inglés
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• Resumen

  • 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.