Optimizing Heart Disease Prediction : A Comparative Study of Machine Learning Models Using Clinical Data
DOI:
https://doi.org/10.62951/ijsme.v1i4.96Keywords:
Heart disease prediction, machine learning, Logistic Regression, K-Nearest Neighbors, health dataAbstract
Cardiovascular disease is a leading cause of death globally, necessitating effective predictive systems. This research aims to analyze the effectiveness of various machine learning (ML) models—Logistic Regression (LR), Random Forest (RF), Naive Bayes (NB), Support Vector Classifier (SVC), and K-Nearest Neighbors (KNN)—in predicting heart disease using publicly available health data. The study involved pre-processing data, training models, and evaluating them using accuracy, precision, recall, F1-score, and G-Mean metrics. The results show that KNN is the most reliable model, with the highest accuracy of 92%. Significant health features were identified, such as chest pain type and maximum heart rate. The study contributes to improving clinical decision support systems by identifying optimal ML models for heart disease prediction.
References
Alarsan, F. I., & Younes, M. (2019). Analysis and classification of heart diseases using heartbeat features and machine learning algorithms. Journal of Big Data, 6(1), 81. https://doi.org/10.1186/s40537-019-0244-x
Ali, L., Niamat, A., Khan, J. A., Golilarz, N. A., Xingzhong, X., Noor, A., Nour, R., & Bukhari, S. A. C. (2019). An Optimized Stacked Support Vector Machines Based Expert System for the Effective Prediction of Heart Failure. IEEE Access, 7, 54007–54014. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2909969
Anjum, N., Siddiqua, C. U., Haider, M., Ferdus, Z., Raju, M. A. H., Imam, T., & Rahman, M. R. (2024). Improving Cardiovascular Disease Prediction through Comparative Analysis of Machine Learning Models. Journal of Computer Science and Technology Studies, 6(2), Article 2. https://doi.org/10.32996/jcsts.2024.6.2.7
Cardiovascular diseases. (n.d.). Retrieved 29 September 2024, from https://www.who.int/health-topics/cardiovascular-diseases
Dutta, A., Batabyal, T., Basu, M., & Acton, S. T. (2020). An efficient convolutional neural network for coronary heart disease prediction. Expert Systems with Applications, 159, 113408. https://doi.org/10.1016/j.eswa.2020.113408
Gárate-Escamila, A. K., Hajjam El Hassani, A., & Andrès, E. (2020). Classification models for heart disease prediction using feature selection and PCA. Informatics in Medicine Unlocked, 19, 100330. https://doi.org/10.1016/j.imu.2020.100330
Gokulnath, C. B., & Shantharajah, S. P. (2019). An optimized feature selection based on genetic approach and support vector machine for heart disease. Cluster Computing, 22(6), 14777–14787. https://doi.org/10.1007/s10586-018-2416-4
Ismail, A., Abdelrazek, S., & El-henawy, I. (2020). BIG DATA ANALYTICS IN HEART DISEASES PREDICTION. Journal of Theoretical and Applied Information Technology, 98, 11.
Le, H. M., Tran, T. D., & Tran, L. V. (2018). AUTOMATIC HEART DISEASE PREDICTION USING FEATURE SELECTION AND DATA MINING TECHNIQUE. Journal of Computer Science and Cybernetics, 34(1), Article 1. https://doi.org/10.15625/1813-9663/34/1/12665
Rahman, B., Hendric Spits Warnars, H. L., Subirosa Sabarguna, B., & Budiharto, W. (2021). Heart Disease Classification Model Using K-Nearest Neighbor Algorithm. 2021 Sixth International Conference on Informatics and Computing (ICIC), 1–4. https://doi.org/10.1109/ICIC54025.2021.9632918
Recursion Enhanced Random Forest With an Improved Linear Model (RERF-ILM) for Heart Disease Detection on the Internet of Medical Things Platform | IEEE Journals & Magazine | IEEE Xplore. (n.d.). Retrieved 22 November 2023, from https://ieeexplore.ieee.org/abstract/document/9037283
Repaka, A. N., Ravikanti, S. D., & Franklin, R. G. (2019). Design And Implementing Heart Disease Prediction Using Naives Bayesian. 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), 292–297. https://doi.org/10.1109/ICOEI.2019.8862604
Sekar, J., Aruchamy, P., Sulaima Lebbe Abdul, H., Mohammed, A. S., & Khamuruddeen, S. (2022). An efficient clinical support system for heart disease prediction using TANFIS classifier. Computational Intelligence, 38(2), 610–640. https://doi.org/10.1111/coin.12487
Sireesha, M. (2020). Classification Model for Prediction of Heart Disease using Correlation Coefficient Technique. International Journal of Advanced Trends in Computer Science and Engineering, 9, 2116–2123. https://doi.org/10.30534/ijatcse/2020/185922020
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