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Keyword: Heart disease predictionModel Uncertainty Quantification: A Post Hoc Calibration Approach for Heart Disease Prediction
by Peter Adebayo Odesola, Adewale Alex Adegoke and Idris Babalola
Journal of Engineering Research and Sciences, Volume 4, Issue 12, Page # 25-54, 2025; DOI: 10.55708/js0412003
Abstract: We investigated whether post-hoc calibration improves the trustworthiness of heart-disease risk predictions beyond discrimination metrics. Using a Kaggle heart-disease dataset (n = 1,025), we created a stratified 70/30 train-test split and evaluated six classifiers, Logistic Regression, Support Vector Machine, k-Nearest Neighbors, Naive Bayes, Random Forest, and XGBoost. Discrimination was quantified by stratified 5-fold cross-validation with… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Real-Time Acquisition and Classification of Electrocardiogram Signal
by Sheikh Md. Rabiul Islam, Akram Hossain and Asif Abdullah
Journal of Engineering Research and Sciences, Volume 1, Issue 11, Page # 8-15, 2022; DOI: 10.55708/js0111002
Abstract: Cardiovascular disease (CVD) is the leading cause of death. The transition in cardiovascular disease threatens the economies of the less developed world. An electrocardiogram (ECG) machine is a device that checks the patient's heart rhythm and electrical activity. ECG signals give crucial information about the heart and numerous cardiac problems, such as coronary artery disease,… Read More
(This article belongs to the Section Biomedical Engineering (BIE))