Editorial: Computational modelling of cardiovascular hemodynamics and machine learning

Artificial Intelligence (A.I.) holds promises in many fields, especially in the health sector. Here, pattern recognition of complex problems—a major strength of A.I. is what makes A.I. so useful. Despite its promises, applying A.I. to the health sector comes with specific challenges, of which the papers in the current issue aim to provide solutions (1–3). This editorial will offer specific background theory on A.I. to better understand the solutions offered in this issue

OCT for the Identification of Vulnerable Plaque in Acute Coronary Syndrome

AbstractAfter 2 decades of development and use in interventional cardiology research, optical coherence tomography (OCT) has now become a core intravascular imaging modality in clinical practice. Its unprecedented spatial resolution allows visualization of the key components of the atherosclerotic plaque that appear to confer “vulnerability” to rupture—namely the thickness of the fibrous cap, size of the necrotic core, and the presence of macrophages. The utility of OCT in the evaluation of plaque composition can provide insights into the pathophysiology of acute coronary syndrome and the healing that occurs thereafter. A brief summary of the principles of OCT technology and a comparison with other intravascular imaging modalities is presented. The review focuses on the current evidence for the use of OCT in identifying vulnerable plaques in acute coronary syndrome and its limitations

Editorial: Research reproducibility and preventing fraud.

SCOPUS: ed.jinfo:eu-repo/semantics/publishe