Early Detection of Coronary Heart Disease Based on Machine Learning Methods

Basit Öğe Kaydı
dc.contributor.authorYılmaz, Rustem
dc.contributor.authorYağın, Fatma Hilal
dc.date.accessioned2024-08-04T19:53:15Z
dc.date.available2024-08-04T19:53:15Z
dc.date.issued2022
dc.departmentİnönü Üniversitesien_US
dc.description.abstractAim: Heart disease detection using machine learning methods has been an outstanding research topic as heart diseases continue to be a burden on healthcare systems around the world. Therefore, in this study, the performances of machine learning methods for predictive classification of coronary heart disease were compared.Material and Method: In the study, three different models were created with Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM) algorithms for the classification of coronary heart disease. For hyper parameter optimization, 3-repeats 10-fold repeated cross validation method was used. The performance of the models was evaluated based on Accuracy, F1 Score, Specificity, Sensitivity, Positive Predictive Value, Negative Predictive Value, and Confusion Matrix (Classification matrix).Results: RF 0.929, SVM 0.897 and LR 0.861 classified coronary heart disease with accuracy. Specificity, Sensitivity, F1-score, Negative predictive and Positive predictive values of the RF model were calculated as 0.929, 0.928, 0.928, 0.929 and 0.928, respectively. The Sensitivity value of the SVM model was higher compared to the RF. Conclusion: Considering the accurate classification rates of Coronary Heart disease, the RF model outperformed the SVM and LR models. Also, the RF model had the highest sensitivity value. We think that this result, which has a high sensitivity criterion in order to minimize overlooked heart patients, is clinically very important.en_US
dc.identifier.doi10.37990/medr.1011924
dc.identifier.endpage6en_US
dc.identifier.issn2687-4555
dc.identifier.issue1en_US
dc.identifier.startpage1en_US
dc.identifier.trdizinid1124976en_US
dc.identifier.urihttps://doi.org/10.37990/medr.1011924
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/1124976
dc.identifier.urihttps://hdl.handle.net/11616/89597
dc.identifier.volume4en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofMedical records-international medical journal (Online)en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleEarly Detection of Coronary Heart Disease Based on Machine Learning Methodsen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

TR-Dizin İndeksli Yayınlar Koleksiyonu