AIMC Topic: Emergency Service, Hospital
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A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department.
Scientific reports
Feb 10, 2024
This study addresses the challenges associated with emergency department (ED) overcrowding and emphasizes the need for efficient risk stratification tools to identify high-risk patients for early intervention. While several scoring systems, often bas...
Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques.
BMC medical informatics and decision making
Feb 8, 2024
BACKGROUND: The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet mental health needs. Ac...
Machine learning models for predicting unscheduled return visits to an emergency department: a scoping review.
BMC emergency medicine
Jan 30, 2024
BACKGROUND: Unscheduled return visits (URVs) to emergency departments (EDs) are used to assess the quality of care in EDs. Machine learning (ML) models can incorporate a wide range of complex predictors to identify high-risk patients and reduce error...
Nonradiology Health Care Professionals Significantly Benefit From AI Assistance in Emergency-Related Chest Radiography Interpretation.
Chest
Jan 29, 2024
BACKGROUND: Chest radiographs (CXRs) are still of crucial importance in primary diagnostics, but their interpretation poses difficulties at times.
Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof-of-concept.
European journal of trauma and emergency surgery : official publication of the European Trauma Society
Jan 24, 2024
PURPOSE: Early administration and protocolization of massive hemorrhage protocols (MHP) has been associated with decreases in mortality, multiorgan system failure, and number of blood products used. Various prediction tools have been developed for th...
Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department.
Scandinavian journal of trauma, resuscitation and emergency medicine
Jan 23, 2024
BACKGROUND: Many prediction models have been developed to help identify emergency department (ED) patients at high risk of poor outcome. However, these models often underperform in clinical practice and their actual clinical impact has hardly ever be...
Repeatability, reproducibility, and diagnostic accuracy of a commercial large language model (ChatGPT) to perform emergency department triage using the Canadian triage and acuity scale.
CJEM
Jan 11, 2024
PURPOSE: The release of the ChatGPT prototype to the public in November 2022 drastically reduced the barrier to using artificial intelligence by allowing easy access to a large language model with only a simple web interface. One situation where Chat...
Evaluating the Reliability of a Remote Acuity Prediction Tool in a Canadian Academic Emergency Department.
Annals of emergency medicine
Jan 3, 2024
STUDY OBJECTIVE: There is increasing interest in harnessing artificial intelligence to virtually triage patients seeking care. The objective was to examine the reliability of a virtual machine learning algorithm to remotely predict acuity scores for ...
Application of Machine Learning Techniques to Development of Emergency Medical Rapid Triage Prediction Models in Acute Care.
Computers, informatics, nursing : CIN
Jan 1, 2024
Given the critical and complex features of medical emergencies, it is essential to develop models that enable prompt and suitable clinical decision-making based on considerable information. Emergency nurses are responsible for categorizing and priori...
Applications of natural language processing at emergency department triage: A narrative review.
PloS one
Dec 14, 2023
INTRODUCTION: Natural language processing (NLP) uses various computational methods to analyse and understand human language, and has been applied to data acquired at Emergency Department (ED) triage to predict various outcomes. The objective of this ...
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