Detection of Heart Disease Using ANN

Abstract

Heart disease remains one of the leading causes of mortality worldwide. Early detection and accurate diagnosis are crucial for effective treatment and prevention of cardiac complications. Artificial neural networks (ANNs) have emerged as powerful tools for heart disease detection, leveraging their ability to learn complex patterns from data. This chapter comprehensively reviews recent studies and developments in the application of ANNs for heart disease detection, highlighting their strengths, challenges, and future directions. The chapter also explores opportunities for the field, imagining the use of federated learning for collaborative model development, the integration of AI-driven decision support systems into standard clinical workflows, and the use of explainable AI techniques to improve model interpretability. It investigates a number of methods, such as the integration of multimodal data sources, convolutional neural networks (CNNs) for image-based diagnosis, risk prediction models, and ECG analysis.

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