Abstract
For many centuries, one of the goals of humankind has been to develop machines, where the engineers and scientists are trying to develop intelligent machines. Artificial neural systems are present-day examples of such machines that have great potential to further improve the quality of our life. Stethoscope is a tool that interpretation by a physician of heart sounds as a fundamental component in cardiac diagnosis. It is, however, a difficult skill to acquire. In this work, the presented study for a system intended to aid in heart sound classification based on artificial neural network (ANN).Where it is contain on three steps. The information acquire is the first step which included recording the heart sound from the patient by the sonoketle phone , where the sound heart can be heard and can record by small record instrument. The second step is analysis step, in which the sound wave file analyzed to get (11) parameter which represents the input to the third step (classification step). In classification step we can recognize the class which the sound wave files belongs to it. heart sounds of (64) subjects divided into two groups normal (20) subjects and heart valve diseases (44) subjects analysis and take times and frequencies as 11 node parameters that interred to input of network .The accurate result was obtained accurate classifier (P<0.001) with hidden node equal to 11, momentum and learning rate equal to 0.2, 0.7, 0.3 and 0.5 respectively with total error equal to 0.39.
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