Abstract
Heart disease has become one of the leading causes of death worldwide in recent years, despite the increased use of high technology in healthcare systems and medical gadgets. Overcrowding and a lack of health infrastructure in emerging countries’ hospitals are likely to hinder patients from visiting the doctor on a regular basis, causing many difficulties in the prevention and detection of heart-related illnesses. This study intends to offer a UNISON data-driven framework that blends digital transformation mechanisms and machine learning technologies to diagnose heart attacks or abnormal heartbeats in order to empower human workforce and increase the efficiency of the healthcare system.
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