Background Machine learning (ML) is increasingly used in research for subtype definition
and risk prediction, particularly in cardiovascular diseases. No existing ML models are …

Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention
studies over the past decades to evaluate and identify an association of systemic …

Financial fraud is escalating as financial services and operations grow. Despite preventive
actions and security measures deployed to mitigate financial fraud, fraudsters are learning …

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 …

Introduction. Hematological indices including red cell distribution width and neutrophil to
lymphocyte ratio are proven to be associated with outcomes of acute coronary syndrome …

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

Aims Identification of high-risk patients and individualized decision support based on
objective criteria for rapid discharge after transcatheter aortic valve implantation (TAVI) are …

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 …

Background Acute coronary syndrome is the topmost cause of death worldwide; therefore, it
is necessary to predict major adverse cardiovascular events and cardiovascular deaths in …

Artificial intelligence (AI) has been hailed as the fourth industrial revolution and its influence
on people's lives is increasing. The research on AI applications in medicine is progressing …