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Service de néphrologie, Département de médecine, Hôpitaux universitaires de Genève, Genève 14.

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Background And Aim: Coronary artery bypass grafting (CABG) is a key treatment for coronary artery disease, but accurately predicting patient survival after the procedure presents significant challenges. This study aimed to systematically review articles using machine learning techniques to predict patient survival rates and identify factors affecting these rates after CABG surgery.

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