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 …

Healthcare Associated Infection (HAI) is a major health problem in several departments of
the hospital sector. These infections cause prolonged length of stay (LOS), complications …

Objectives The purpose of this study was to identify septic patients at greater risk of longer
stay in the ICU, using a random forest machine learning algorithm. Methods This …

Purpose Studies have shown that a small percentage of ICU patients have prolonged length
of stay (LoS) and account for a large proportion of resource use. Therefore, the identification …

Abstract According to the World Health Organization (WHO), patient Length of Stay (LOS) in
hospitals is an important performance measurement and monitoring indicator. Prolonged …

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 …

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 …

Accurately estimating the length of stay (LOS) of patients admitted to the intensive care unit
(ICU) in relation to their health status helps healthcare management allocate appropriate …

The length-of-stay (LOS) is critical for patient care and accommodation in the intensive care
unit (ICU). In this work, we developed a framework to predict the LOS using the Medical …

Background In-hospital mortality, prolonged length of stay (LOS), and 30-day readmission
are common outcomes in the intensive care unit (ICU). Traditional scoring systems and …