학술논문
An Effective FL-CNN Based Data Securing Model for Heart Disease Prediction
Document Type
Conference
Author
Source
2023 6th International Conference on Contemporary Computing and Informatics (IC3I) Contemporary Computing and Informatics (IC3I), 2023 6th International Conference on. 6:1862-1866 Sep, 2023
Subject
Language
Abstract
Cardiovascular disease is the leading cause of death worldwide, according to the WHO. Coronary heart disease is most dangerous. 2015 saw 360,000 US heart attack deaths. Effective heart disease treatment prevents global deaths. An updated FL-CNN model improved cardiac disease diagnosis and prognosis for doctors and patients. Hospitals cannot disclose patient data for security and privacy reasons. Thus, centralizing data is hard. Federated Learning can train machine learning and deep learning models using massive volumes of distributed data. On the UCI Cleveland dataset, CNN with Federated Learning achieves 94.99% accuracy, while CNN with centralized learning achieves 97% accuracy.