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Cardiovascular disease incidence prediction by machine learning and statistical techniques: a 16-year cohort study from eastern Mediterranean region., , , , , and . BMC Medical Informatics Decis. Mak., 23 (1): 72 (December 2023)Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: A clinician-in-the-loop scenario with a belief-uncertainty fusion paradigm., , , , , , , , , and 5 other author(s). Inf. Fusion, (September 2023)Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks., , , , , and . Comput. Math. Methods Medicine, (2013)Which risk factor best predicts coronary artery disease using artificial neural network method?, , , , , , , , , and 4 other author(s). BMC Medical Informatics Decis. Mak., 24 (1): 52 (December 2024)Non-invasive detection of coronary artery disease in high-risk patients based on the stenosis prediction of separate coronary arteries., , , , , , and . Comput. Methods Programs Biomed., (2018)FH-TabNet: Multi-Class Familial Hypercholesterolemia Detection via a Multi-Stage Tabular Deep Learning., , , , and . CoRR, (2024)Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991-2020., , , , , , , , , and 6 other author(s). Comput. Biol. Medicine, (2021)Coronary artery disease detection using computational intelligence methods., , , , , , , , and . Knowl. Based Syst., (2016)NE-nu-SVC: A New Nested Ensemble Clinical Decision Support System for Effective Diagnosis of Coronary Artery Disease., , , and . IEEE Access, (2019)Automated detection of shockable ECG signals: A review., , , , , , , , , and 5 other author(s). Inf. Sci., (2021)