Cardiovascular diseases (CVDs) have been ranked as the leading cause for deaths. The early diagnosis of CVDs is a crucial task in the medical practice.
In this dilemma, we propose a federated learning (FL) framework for the heart sound classification task. To the best of our knowledge, this is the first time to ...
Jul 16, 2022 · CWT's ability to capture both shortterm and long-term variations in frequency content makes it particularly suitable for analysing dynamic and ...
A federated learning (FL) framework for the heart sound classification task and the impact of data distribution across collaborative institutions on model ...
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Fingerprint. Dive into the research topics of 'A Federated Learning Paradigm for Heart Sound Classification'. Together they form a unique fingerprint.
Fingerprint. Dive into the research topics of 'A Federated Learning Paradigm for Heart Sound Classification'. Together they form a unique fingerprint.
To this end, vertical federated learning is utilised to address the issues of model interpretability and data scarcity. Experimental results demonstrate that, ...
This paradigm involves training models using a combination of labeled and unlabeled data, making it particularly relevant for medical applications with limited ...
A distributed machine learning system called federated learning enables several parties to train a machine learning model independently of one another.
The research included the use of deep learning (DL) algorithms and CNN architectures for the automatic detection of cardiac sounds, monitoring heart rate ...