Abstract In healthcare, Intensive Care Unit (ICU) bed management is a necessary task
because of the limited budget and resources. Predicting the remaining Length of Stay (LoS) …

This study aimed to construct machine learning (ML) models for predicting prolonged length
of stay (pLOS) in intensive care units (ICU) among general ICU patients. A multicenter …

Objectives To test the hypothesis that implementation of a cytochrome P-450 2D6 (CYP2D6)
genotype–guided perioperative metoprolol administration will reduce the risk of …

It was aimed at the clinical value of predictive nursing and Algoplaque hydrocolloid dressing
(AHD) combined with nanosilver antibacterial gel in treating medical device‐related …

Objectives: Risk assessment models for cardiac surgery do not distinguish between degrees
of liver dysfunction. We have previously shown that preoperative liver stiffness is associated …

Background The long-term outcomes for patients after coronary artery bypass grafting
(CABG) have been received more and more concern. The existing prediction models are …

Background: Cardiac surgery is resource intensive and often requires multidisciplinary
involvement to facilitate discharge. To facilitate evidence-based resource planning, we …

Background: Open-heart surgery is associated with life-threatening complications, and
providing nonstandard nursing care without any plan for patients undergoing this type of …

Background Predicting the length of stay in advance will not only benefit the hospitals both
clinically and financially but enable healthcare providers to better decision-making for …

Understanding the length of stay of severe patients who require general anesthesia is key to
enhancing health outcomes. Here, we aim to discover how machine learning can support …