Additional Study Information: Stethoscopes are one of the most common and non-invasive tools used by healthcare providers in examining the circulatory and respiratory systems in patients. There are several digital stethoscopes on the market that can interface with smartphones, allowing anyone to listen and visualize and listen to the internal sounds produced by their own body. However, being able to accurately detect abnormal sounds from normal bodily sounds requires years of clinical training. As such, a person would not be able to screen themselves through listening to their heart sounds even if they possess any of the digital stethoscopes that are readily available on the consumer market; they would still need to seek a healthcare provider. We propose and design a non-invasive digital stethoscope platform powered by artificial intelligence (AI) with the goal of enabling the general population to screen themselves for abnormal functioning of their body internally. Our system runs AI detection and acoustic filtering algorithms to enhance and detect abnormal sounds that indicate conditions such as heart murmurs, fluid build-up in lungs, and hyper/hypo activity in bowel movements.