Introduction. Coronary artery disease (CAD) is one of the main causes of death all over the
world. One way to reduce the mortality rate from CAD is to predict its risk and take effective …

As the world produces exabytes of data, there is a growing need to find new methods that
are more suitable for dealing with complex datasets. Artificial intelligence (AI) has significant …

Aims This study aimed to review the performance of machine learning (ML) methods
compared with conventional statistical models (CSMs) for predicting readmission and …

Background Traditional risk assessment tools often lack accuracy when predicting the short-
and long-term mortality following a non-ST-segment elevation myocardial infarction …

Background Acute coronary syndromes (ACS) are the leading cause of global death.
Optimizing mortality risk prediction and early identification of high-risk patients is essential …

Purpose Systemic inflammatory response index (SIRI) was an independent predictor of the
prognosis of many diseases. Inflammatory prognostic index (IPI) was a new inflammatory …

Aims Systemic inflammatory response, identified by increased total leucocyte counts, was
shown to be a strong predictor of mortality after transcatheter aortic valve implantation …

Acute coronary syndrome (ACS) is a leading cause of mortality and morbidity. Predicting the
associated risks of patients with chest pain using electronic health record data can help …

Background Risk prediction following ST-Elevation Myocardial Infarction (STEMI) in
resource limited countries is critical to identify patients at an increased risk of mortality who …

Background Clinical risk assessment with quantitative formal risk scores may add to intuitive
physician risk assessment and are advised by the international guidelines for the …