Book Title: Contemporary Research Across Disciplines
Editors: Dr. R. Saravana Selvakumar and Mr. R. Venkatesan
ISBN: 978-81-978738-1-2
Chapter: 5
DOI: https://doi.org/10.59646/crc5/278
Author: Mrs. M. Gandhimathi, Assistant Professor and Head, Department of Computer Applications, G. Venakataswamy Naidu College (Autonomous), Kovilpatti, Tamil Nadu, India.
Abstract
In both advanced and developing countries, cardiovascular diseases have become the leading cause of death in recent decades. Early detection and ongoing medical monitoring can reduce mortality rates. However, consistent diagnosis and continuous patient monitoring are challenging due to the need for extensive review, time, and expertise. This survey proposes a cloud-based coronary artery disease (CAD) management system utilizing artificial intelligence techniques. A robust AI approach, derived from analyzing several machine learning algorithms, is designed to detect CAD accurately. Ten-fold cross-validation was employed to evaluate CAD representation in two widely used open datasets, validating the proposed algorithm. The SVM algorithm demonstrated sensitivity and specificity of 97.50% and 94.94%, respectively, with an accuracy of 97.53%. Using Arduino, a real-time patient monitoring system was developed to detect various parameters, such as internal temperature, blood pressure, humidity, and heart rate, continuously monitoring a heart patient 24/7. The system transmits recorded data to a central server that is updated regularly.
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