Predicting a patient's hospital length of stay (LoS) can help manage staffing. In this paper,
we explore LoS prediction for a large group of patients admitted non-electively. We use …

Objective This study aimed to assess the performance improvement for machine learning-
based hospital length of stay (LOS) predictions when clinical signs written in text are …

Objective To develop a predictive model for real-time predictions of length of stay, mortality,
and readmission for hospitalized patients using electronic health records (EHRs). Materials …

Objective: The objective of this study was to evaluate the incremental predictive power of
electronic medical record (EMR) data, relative to the information available in more easily …

Background: Length of stay (LOS) is a common measure of hospital resource utilization.
Most methods for risk-adjusting LOS are limited by the use of only administrative data …

Objective Hospital capacity management depends on accurate real-time estimates of
hospital-wide discharges. Estimation by a clinician requires an excessively large amount of …

Obstetric care refers to the care provided to patients during ante-, intra-, and postpartum
periods. Predicting length of stay (LOS) for these patients during their hospitalizations can …

Length of stay (LOS) estimates are important for patients, doctors and hospital
administrators. However, making accurate estimates of LOS can be difficult for medical …

Objective Hospitals are challenged to provide timely patient care while maintaining high
resource utilization. This has prompted hospital initiatives to increase patient flow and …

Abstract Objective The In-hospital length of stay (LOS) is expected to increase as
cardiovascular diseases complexity increases and the population ages. This will affect …