AIMC Topic: Emergency Service, Hospital
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Explainable Deep Learning Model for Predicting Serious Adverse Events in Hospitalized Geriatric Patients Within 72 Hours.
Clinical interventions in aging
Jun 12, 2024
BACKGROUND: The global aging population presents a significant challenge, with older adults experiencing declining physical and cognitive abilities and increased vulnerability to chronic diseases and adverse health outcomes. This study aims to develo...
Managing low-acuity patients in an Emergency Department through simulation-based multiobjective optimization using a neural network metamodel.
Health care management science
Jun 10, 2024
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...
Leveraging graph neural networks for supporting automatic triage of patients.
Scientific reports
May 31, 2024
Patient triage is crucial in emergency departments, ensuring timely and appropriate care based on correctly evaluating the emergency grade of patient conditions. Triage methods are generally performed by human operator based on her own experience and...
Appropriate use of blood cultures in the emergency department through machine learning (ABC): study protocol for a randomised controlled non-inferiority trial.
BMJ open
May 31, 2024
INTRODUCTION: The liberal use of blood cultures in emergency departments (EDs) leads to low yields and high numbers of false-positive results. False-positive, contaminated cultures are associated with prolonged hospital stays, increased antibiotic us...
Implementation considerations for the adoption of artificial intelligence in the emergency department.
The American journal of emergency medicine
May 24, 2024
OBJECTIVE: Artificial intelligence (AI) has emerged as a potentially transformative force, particularly in the realm of emergency medicine (EM). The implementation of AI in emergency departments (ED) has the potential to improve patient care through ...
A machine learning-based lung ultrasound algorithm for the diagnosis of acute heart failure.
Internal and emergency medicine
May 23, 2024
Lung ultrasound (LUS) is an effective tool for diagnosing acute heart failure (AHF). However, several imaging protocols currently exist and how to best use LUS remains undefined. We aimed at developing a lung ultrasound-based model for AHF diagnosis ...
Using a clinical narrative-aware pre-trained language model for predicting emergency department patient disposition and unscheduled return visits.
Journal of biomedical informatics
May 19, 2024
The increasing prevalence of overcrowding in Emergency Departments (EDs) threatens the effective delivery of urgent healthcare. Mitigation strategies include the deployment of monitoring systems capable of tracking and managing patient disposition to...
Can artificial intelligence help ED nurses more accurately triage patients?
Nursing
May 17, 2024
The Emergency Severity Index (ESI) is the most popular tool used to triage patients in the US and abroad. Evidence has shown that ESI has its limitations in correctly assigning acuity. To address this, AI can be incorporated into the triage process, ...
Applying natural language processing to identify emergency department and observation encounters for worsening heart failure.
ESC heart failure
May 13, 2024
AIMS: Worsening heart failure (WHF) events occurring in non-inpatient settings are becoming increasingly recognized, with implications for prognostication. We evaluate the performance of a natural language processing (NLP)-based approach compared wit...
Can Artificial Intelligence Be Utilized to Predict Real-Time Adverse Outcomes in Individuals Arriving at the Emergency Department With Hyperglycemic Crises?: Implications for APRN Practice.
Advanced emergency nursing journal
May 9, 2024
This column on translating research into practice is crafted to offer advanced practice registered nurses an analysis of current research topics that hold practical relevance for emergency care settings. The article titled "Using Artificial Intellige...
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