Cardiogenic shock is a complex syndrome manifesting with distinct phenotypes depending
on the severity of the primary cardiac insult and the underlying status. As long as therapeutic …

Background: Artificial intelligence (AI) can radically change almost every aspect of the
human experience. In the medical field, there are numerous applications of AI and …

Aims Myocardial infarction and heart failure are major cardiovascular diseases that affect
millions of people in the USA with morbidity and mortality being highest among patients who …

Artificial intelligence (AI) is an emerging technology with numerous healthcare applications.
AI could prove particularly useful in the cardiac intensive care unit (CICU) where its capacity …

Cardiogenic shock (CS) carries a 30–50% in‐hospital mortality rate, with little improvement
in outcomes in the last decade. Challenges in improving outcomes are closely linked to the …

Patients with cardiogenic shock (CS) present with critical hemodynamic compromise with
low cardiac output (CO) resulting in end-organ dysfunction. Prognosis is closely related to …

Cardiogenic shock (CS) may have a negative impact on mortality in patients with heart
failure (HF) or acute myocardial infarction (AMI). Early prediction of CS can result in …

Cardiogenic shock (CS) is a complex, multisystem disorder precipitated by hypoperfusion
from cardiac dysfunction. Our current approach to defining and treating CS encompasses all …

Background The aim of this study was to use five machine learning approaches and logistic
regression to design and validate the acute kidney injury (AKI) prediction model for critically …

Cardiogenic shock, resulting from cardiac dysfunction, poses a dire threat during cardiac
emergencies, necessitating prompt inpatient transfers to intensive care units and aggressive …