Federated Learning Meets IoT: A Novel Approach to Cardiovascular Disease Prediction

Cardiovascular disease is one of the most significant causes of mortality worldwide, considering the lives of millions of humans each year. The chance of getting cardiovascular disease rises as people’s life style and their physical health declines. Prediction of this risk can now be achieved by early identification and treatment with the use of ML and AI-based predictive models. With regard to the prediction of cardiovascular disease events in conjunction with IoT devices along with ensemble models combined with federated learning model is suggested to get more performance. This paper explores various methodologies to predict cardiovascular events, emphasizing federated learning (FL) and its application in CVD detection. This paper also reviews the advantages and challenges of federated learning in healthcare along with IoT wearables features & applications.

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Publication Details

Published
2024-11-28
DOI
https://doi.org/10.1109/icaiccit64383.2024.10912271
Citations
2
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.80
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article

Federated Learning Meets IoT: A Novel Approach to Cardiovascular Disease Prediction

G. Muneeswari, Gorapalli Srinivasa Rao
2 citations
ECG Monitoring and Analysis
0.80
article

Federated Learning Meets IoT: A Novel Approach to Cardiovascular Disease Prediction

G. Muneeswari, Gorapalli Srinivasa Rao
article en
2 citations

Abstract

Cardiovascular disease is one of the most significant causes of mortality worldwide, considering the lives of millions of humans each year. The chance of getting cardiovascular disease rises as people’s life style and their physical health declines. Prediction of this risk can now be achieved by early identification and treatment with the use of ML and AI-based predictive models. With regard to the prediction of cardiovascular disease events in conjunction with IoT devices along with ensemble models combined with federated learning model is suggested to get more performance. This paper explores various methodologies to predict cardiovascular events, emphasizing federated learning (FL) and its application in CVD detection. This paper also reviews the advantages and challenges of federated learning in healthcare along with IoT wearables features & applications.

SRM University (IN), VIT-AP University
Openalex Percentile: Top 21%
ECG Monitoring and Analysis
0.80
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