Artificial Intelligence in Medicine: Real Time Electronic Stethoscope for Heart Diseases Detection

Diseases of the cardiovascular system are one major causes death worldwide. These diseases could be quickly detected by changes in sound created action heart. This dynamic auscultations need extensive professional knowledge and emphasis on listening skills. There is also an unmet requirement for a compact cardiac condition early warning device. In this paper, we propose prototype digital stethoscopic diagnosis abnormalities real time using machine learning methods. consists three subsystems that interact with each other (1) portable subsystem electronic stethoscope, (2) decision-making subsystem, (3) displaying visualizing results understandable form. The stethoscope captures patient’s phonocardiographic sounds, filters digitizes them, then sends resulting sounds to system. classifies into normal abnormal techniques, as result identifies heart sounds. display visualization demonstrates obtained way not only medical staff, but patients recommends further actions patients. As study, can diagnose accuracy more than 90%. More accurately, proposed identify 93.5% accuracy, 93.25% accuracy. Moreover, speed key benefit 15 s adequate examination.