The depth and breadth of data produced in the modern cardiac intensive care unit (CICU)
poses challenges to clinicians and researchers. Artificial intelligence (AI) and machine …

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 …

Abstract Machine learning can predict outcomes and determine variables contributing to
precise prediction, and can thus classify patients with different risk factors of outcomes. This …

The COVID-19 virus has spread rapidally throughout the world. Managing resources is one
of the biggest challenges that healthcare providers around the world face during the …

Sepsis is an organ failure disease caused by an infection resulting in extremely high
mortality. Machine learning algorithms XGBoost and LightGBM are applied to construct two …

Background: Patients with sepsis have a high mortality rate. Rapid and effective risk
stratification indicators for sepsis-related death are urgently needed to explored. Blood urea …

Background Post-operative mortality risk assessment for geriatric patients with hip fractures
(HF) is a challenge for clinicians. Early identification of geriatric HF patients with a high risk …

Background Sepsis is a life-threatening condition caused by an abnormal response of the
body to infection and imposes a significant health and economic burden worldwide due to its …

Study Design. A retrospective cohort study. Objective. The objective of the study was to
develop machine-learning (ML) classifiers for predicting prolonged intensive care unit (ICU) …

Background: Accurate planning of the duration of stays at intensive care units is of utmost
importance for resource planning. Currently, the discharge date used for resource …