CardioScope

Overview

Cardiovascular disease (CVD) is one of the leading causes of morbidity worldwide, affecting over half a billion individuals globally and approximately 127.9 million adults in the United States. Despite its prevalence, many cardiovascular conditions remain undiagnosed in their early stages due to barriers such as high healthcare costs, limited access to diagnostic equipment, and shortages of trained medical professionals. As a result, an estimated 36% of U.S. adults delay or avoid necessary medical care each year because of financial constraints. This project focuses on developing an artificial intelligence–based screening application that analyzes heart sound recordings obtained through a stethoscope to classify cardiac function as normal or potentially abnormal. The system applies machine learning techniques to identify acoustic patterns associated with common cardiac irregularities, enabling rapid, non-invasive assessment at the point of care. By providing an affordable and accessible screening tool, this technology has the potential to expand early cardiovascular assessment in primary care settings and underserved communities. The proposed system may reduce unnecessary referrals and advanced diagnostic testing for low-risk individuals while allowing earlier identification of high-risk patients who require further evaluation through electrocardiography or echocardiography. Overall, this project aims to improve early detection of cardiovascular disease and increase equity in access to preventive cardiac care.

Competition history

• CSEF 2026 Medicine & Physiology (Senior Division) · Entry S-15-07

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