AIMC Topic: Triage
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Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score.
BMC emergency medicine
Jan 23, 2025
BACKGROUND: Traumatic injuries are a leading cause of morbidity and mortality globally, with a disproportionate impact on populations in low- and middle-income countries (LMICs). The Kampala Trauma Score (KTS) is frequently used for triage in these s...
Evaluation of Generative Artificial Intelligence Models in Predicting Pediatric Emergency Severity Index Levels.
Pediatric emergency care
Jan 7, 2025
OBJECTIVE: Evaluate the accuracy and reliability of various generative artificial intelligence (AI) models (ChatGPT-3.5, ChatGPT-4.0, T5, Llama-2, Mistral-Large, and Claude-3 Opus) in predicting Emergency Severity Index (ESI) levels for pediatric eme...
The role of artificial intelligence in gynecologic and obstetric emergencies.
European journal of obstetrics, gynecology, and reproductive biology
Jan 6, 2025
OBJECTIVE: To investigate the potential of artificial intelligence (AI) in emergency medicine, focusing on its utility in triaging and managing acute gynecologic and obstetric emergencies.
Clinicians' perspectives on the use of artificial intelligence to triage MRI brain scans.
European journal of radiology
Jan 6, 2025
Artificial intelligence (AI) tools can triage radiology scans to streamline the patient pathway and also relieve clinician workload. Validated AI tools can mitigate the delays in reporting scans by flagging time-sensitive and actionable findings. In ...
Interpretable machine learning for predicting sepsis risk in emergency triage patients.
Scientific reports
Jan 6, 2025
The study aimed to develop and validate a sepsis prediction model using structured electronic medical records (sEMR) and machine learning (ML) methods in emergency triage. The goal was to enhance early sepsis screening by integrating comprehensive tr...
Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study.
BMC emergency medicine
Jan 5, 2025
BACKGROUND: In Sweden with about 10 million inhabitants, there are about one million primary ambulance missions every year. Among them, around 10% are assessed by Emergency Medical Service (EMS) clinicians with the primary symptom of dyspnoea. The ri...
Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study.
Journal of medical Internet research
Dec 31, 2024
BACKGROUND: Hospitals use triage systems to prioritize the needs of patients within available resources. Misclassification of a patient can lead to either adverse outcomes in a patient who did not receive appropriate care in the case of undertriage o...
Machine-learning based prediction of appendicitis for patients presenting with acute abdominal pain at the emergency department.
World journal of emergency surgery : WJES
Dec 23, 2024
BACKGROUND: Acute abdominal pain (AAP) constitutes 5-10% of all emergency department (ED) visits, with appendicitis being a prevalent AAP etiology often necessitating surgical intervention. The variability in AAP symptoms and causes, combined with th...
Evaluating LLM-based generative AI tools in emergency triage: A comparative study of ChatGPT Plus, Copilot Pro, and triage nurses.
The American journal of emergency medicine
Dec 19, 2024
BACKGROUND: The number of emergency department (ED) visits has been on steady increase globally. Artificial Intelligence (AI) technologies, including Large Language Model (LLMs)-based generative AI models, have shown promise in improving triage accur...
Using machine learning and natural language processing in triage for prediction of clinical disposition in the emergency department.
BMC emergency medicine
Dec 18, 2024
BACKGROUND: Accurate triage is required for efficient allocation of resources and to decrease patients' length of stay. Triage decisions are often subjective and vary by provider, leading to patients being over-triaged or under-triaged. This study de...
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