Background Risk stratification plays a central role in anesthetic evaluation. The use of Big
Data and machine learning (ML) offers considerable advantages for collection and …

Modern Intensive Care Units (ICUs) provide continuous monitoring of critically ill patients
susceptible to many complications affecting morbidity and mortality. ICU settings require a …

Introduction This study aimed to develop and validate an interpretable machine-learning
model based on clinical features for early predicting in-hospital mortality in critically ill …

Background: Mechanically ventilated patients in the intensive care unit (ICU) have high
mortality rates. There are multiple prediction scores, such as the Simplified Acute Physiology …

Introduction Septic patients requiring intensive care unit (ICU) readmission are at high risk of
mortality, but research focusing on the association of ICU readmission due to sepsis and …

Sepsis is a life-threatening disease that is associated with organ dysfunction. It occurs due to
the body's dysregulated response to infection. It is difficult to identify sepsis in its early …

Background and objectives Sepsis is accompanied by a considerably high risk of mortality in
the short term, despite the availability of recommended mortality risk assessment tools …

Background Fragility hip fracture increases morbidity and mortality in older adult patients,
especially within the first year. Identification of patients at high risk of death facilitates …

Background Sepsis poses a critical threat to hospitalized patients, particularly those in the
Intensive Care Unit (ICU). Rapid identification of Sepsis is crucial for improving survival …

Background Mechanical ventilation (MV) is vital for critically ill ICU patients but carries
significant mortality risks. This study aims to develop a predictive model to estimate hospital …