Thrilling AI – A novel, signal-based digital biomarker for diagnosing canine heart diseases

Abstract Auscultation methods enable non-invasive diagnosis of diseases, e.g. the heart, based on heartbeat sounds. Regular, early examinations using machine learning techniques could help to detect diseases at an stage prevent serious health conditions and then provide optimal therapy through continuous monitoring. There is already a lot work human data AI algorithms patterns in signals or images. However, there hardly no detecting heart murmurs with digital such as Myxomatous Mitral Valve Disease. In this paper, we present canine auscultation project that aims tool establish baseline classification parameters from audio be used monitor status by analyzing deviations baseline. future, analysis also lead prediction detection other diseases.