Theoretical framework reveals decentralized heart sound abnormality detection for cardiovascular diseases, highlighting collaborative artificial intelligence without data privacy risks.
Early diagnosis of cardiovascular diseases is a crucial task in medical practice. With the application of computer audition in the healthcare field, artificial intelligence (AI) has been applied to clinical non-invasive intelligent auscultation of heart sounds to provide rapid and effective pre-screening. However, AI models generally require large amounts of data which may cause privacy issues. Unfortunately, it is difficult to collect large amounts of healthcare data from a single centre.
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Qiu et al. (2024) studied this question.
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