The broader impact/commercial potential of this I-Corps project is the development of a non-invasive screening tool that will allow physicians to accurately and objectively screen for cardiovascular diseases, regardless of symptom presence. Cardiovascular diseases are often only diagnosed in late stages after heart function is severely diminished. Early detection of asymptomatic patients could lead to less invasive or earlier treatment to prevent disease progression and identify new late-stage patients in need of life-saving procedures. The proposed technology discriminates between abnormal and normal sounds, using artificial intelligence for improved efficiency and accuracy in cardiovascular screening. This I-Corps project is based on the development of an artificial intelligence-based diagnostic algorithm that uses heart sounds recorded from a digital stethoscope, similar to the devices currently used by doctors during routine physical exams, to classify cardiovascular disease stage. The proposed technology uses a database that correlates heart sounds to disease stage and cardiac function. In addition, the proposed technology standardizes and analyzes descriptors of sound to reduce user-dependent disease classification error.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.