Abstract
Recent years have witnessed significant innovation in diagnostic tools driven by the convergence of technological breakthroughs and the demands of the medical industry. The goal of this research is to present the development and validation of a real-time digital stethoscope that is designed to identify cardiovascular problems based on phonocardiograms. The device not only records heart sounds with high precision but also concurrently analyzes acoustic features to identify potential ailments. This is achieved by the application of contemporary signal processing techniques. This method’s clinical potential was confirmed through early testing on a cohort of two hundred patients, revealing a diagnosis accuracy of 94.5% in differentiating normal from pathological cardiac murmurs. The machine learning approaches developed shown a significant sensitivity to subtle murmurs and arrhythmias, which are generally challenging to identify with conventional auscultation techniques. This technique’s most revolutionary feature is its capacity to deliver prompt feedback to healthcare experts. This mitigates the latency associated with manual interpretation and facilitates participation in prompt treatments. It is probable that the gadget would be of the greatest utility in places with few resources, as it would enable access to essential cardiac diagnostics. This is despite its potential applicability in various therapeutic contexts. The study’s findings unequivocally highlight the essential role of digital technology in the integration of traditional medical equipment, thereby facilitating a new era of patient care that is both accessible and of superior quality.