Smart Healthcare System for Cardiovascular Diseases Diagnosis | ||||
| The International Undergraduate Research Conference | ||||
| Volume 6, Issue 6, September 2022, Page 1-7 PDF (1.2 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/iugrc.2022.302715 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Ahmed Tolba1; Ahmed Elmasry1; Yara Mohamed2; Amany Salah1 | ||||
| 1Zagazig, Sharqia, Egypt. | ||||
| 2Zagazig, Sharqi, Egypt. | ||||
| Abstract | ||||
| The World Health Organization (WHO) reported that cardiovascular diseases account for 40% of total deaths in Egypt and 32% of all deaths worldwide . Cardiovascular disease is a major public health concern with significant social and economic implications in terms of healthcare needs, lost productivity, and premature death. According to the Egyptian Vision 2030, healthcare is one of the main pillars for achieving sustainable development. So we decided to develop an intelligent CAD system to improve the diagnosis of cardiovascular diseases in the Egyptian healthcare system. This project presents an innovative edge intelligence system for the automated diagnosis of cardiovascular disease. The system emphasis delivering real-time and low-cost processing of cardiovascular biomarkers to accelerate the initial diagnosis. Then, an elegant service is also provided to afford automated, interpretable, and accurate diagnosis from cardiac biomarkers of critical cases Taking into account the preservation of patient data and protection of the system from hacking. Our system is designed to satisfy the pillars of healthcare sustainability according to the Egyptian Vision 2030. The simulation results obtained from two public benchmarks validate the effectiveness of these approaches in terms of accuracy (99%, 97%) and f1-scores (99%, 98%). | ||||
| Keywords | ||||
| Deep learning (DL); Federated Learning (FL); Explainable Ai; Internet of Health things(IOHT); Cyber-Attacks | ||||
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