Coronary Artery Disease(CAD) Detector

Abstract

Cardiovascular diseases, particularly coronary artery disease (CAD), continue to be a major global health concern, leading to significant mortality and morbidity. This paper proposes a novel approach utilizing advanced machine learning and deep learning techniques to enhance the detection and diagnosis of CAD and other heart-related conditions. The proposed system incorporates real-time heart rate monitoring and early CAD detection through a combination of sensors, an Arduino microcontroller, Bluetooth technology, and sophisticated AI models. These models leverage Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), and a hybrid framework integrating clinical data with ECG analysis. The system features a user-friendly Android application that provides real-time heart rate monitoring and predictive CAD analysis. This research seeks to bridge the technological gap in healthcare by offering an accessible and cost-effective solution for managing CAD, ultimately aiming to improve patient outcomes and overall public health.