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dc.contributor.authorBOUTARFA, MOHAMMED AMIN-
dc.date.accessioned2022-10-11T11:58:54Z-
dc.date.available2022-10-11T11:58:54Z-
dc.date.issued2022-
dc.identifier.urihttp://dspace.univ-guelma.dz/jspui/handle/123456789/13038-
dc.description.abstractHeart diseases are considered as one of the most dangerous diseases as it threatens the organ on which human life depends, and as the diagnosis of diseases depends on medical tests and certain indicators. The cardiac disease diagnosis is considered to be the most complex and difficult, due to the large number of analyzes and indicators in this diagnosis, which has led many researchers to use data mining and machine learning techniques to be able to predict this disease. This prompted us to create a system that allows us to predict cardiac patients from a database of diagnosed patients. This was achieved by using machine learning techniques and applying the PCA method for data processing and preparing the collected data for classification by the KNN algorithm, which allowed us to achieve an accuracy of 97.83%.en_US
dc.language.isofren_US
dc.publisheruniversité de guelmaen_US
dc.subjectApprentissage automatique, maladies cardiaques, maladie cardio-vasculaire, prédiction, classificationen_US
dc.titleSystème intelligent de prédiction des maladies cardiaquesen_US
dc.typeWorking Paperen_US
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