WSEAS Transactions on Systems and Control
Print ISSN: 1991-8763, E-ISSN: 2224-2856
Volume 20, 2025
Heart Disease Prediction in Smart Healthcare System: An Application of Machine Learning and Deep Learning Techniques
Authors: , , ,
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Abstract: Heart disease is a principal cause of illness and mortality worldwide. Early prediction and intervention are vital for active treatment and reducing the mortality rates. Smart healthcare systems offer a hopeful approach to attain this goal by applying machine learning (ML) and deep learning (DL) techniques for the prediction ofheart disease. The present study discovers the application of ML and DL algorithms to examine patient data and predict the heart disease risk. The Machine Learning and deep learning models with voting and stacking classifier, and XGBoost have been applied. We conducted a comprehensive analysis to identify the optimal machine learning algorithm within the considered models. It is observed that, with mean accuracies around 0.82-0.83 and significant low standard deviation, stacking classifier and LR are showing top performance.
Keywords:
Heart Disease, Machine Learning, Deep Learning, Decision Tree (DT), Logistic Regression (LR), Naïve Bayes (NB), XGBoost, Ensemble Learning, Artificial Neural Network (ANN)
Pages: 580-594
DOI: 10.37394/23203.2025.20.57