OBJECTIVES: Emergency department crowding refers to a complex state of congestion associated with a set of performance indicators such as occupation levels, waiting times and specific scores. Among current methods to model it, an objective gap exists...
BACKGROUND: Emergency department (ED) overcrowding remains a critical challenge, leading to delays in patient care and increased operational strain. Current hospital management strategies often rely on reactive decision-making, addressing congestion ...
Emergency department (ED) overcrowding has become a critical issue in hospital management, leading to increased patient wait times and higher rates of individuals leaving without being seen (LWBS). This study aims to identify key factors influencing ...
In open environments, complex and variable backgrounds and dense multi-scale targets are two key challenges for crowd counting. Due to the reliance on supervised learning with labeled data, current methods struggle to adapt to crowd detection in comp...
INTRODUCTION: Overcrowding in emergency departments (ED) is a major public health issue, leading to increased workload and exhaustion for the teams, resulting poor outcomes. It seems interesting to be able to predict the admissions of patients in the...
BMC medical informatics and decision making
Dec 18, 2024
BACKGROUND: Emergency department (ED) overcrowding is an important problem in many countries. Accurate predictions of ED patient arrivals can help management to better allocate staff and medical resources. In this study, we investigate the use of cal...
Monitoring Surveillance video is really time-consuming, and the complexity of typical crowd behaviour in crowded situations makes this even more challenging. This has sparked a curiosity about computer vision-based anomaly detection. This study intro...
This paper deals with Emergency Department (ED) fast-tracks for low-acuity patients, a strategy often adopted to reduce ED overcrowding. We focus on optimizing resource allocation in minor injuries units, which are the ED units that can treat low-acu...
Crowd flow prediction has been studied for a variety of purposes, ranging from the private sector such as location selection of stores according to the characteristics of commercial districts and customer-tailored marketing to the public sector for s...
Neural networks : the official journal of the International Neural Network Society
Dec 20, 2023
Real-world robot applications usually require navigating agents to face multiple destinations. Besides, the real-world crowded environments usually contain dynamic and static crowds that implicitly interact with each other during navigation. To addre...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.