Article

Performance evaluation and benchmarking across 16 large language models on a comprehensive real-world emergency department triage data set

2026-06-28

Abstract excerpt

<title>Abstract</title> <p>Background Emergency department (ED) triage is a high-stakes clinical decision process that determines patient prioritization and resource allocation under time pressure. Large language models (LLMs) have recently been proposed as decision-support tools for triage, yet most evaluations rely on simulated scenarios or curated datasets. Evidence from real-world clinical environments remai...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 38ad3437-ee63-5096-9842-58700f9a2701
DOI: 10.21203/rs.3.rs-9727564/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Performance evaluation and benchmarking across 16 large language models on a comprehensive real-world emergency department triage data setDOI 10.21203/rs.3.rs-9727564/v1Read

Performance evaluation and benchmarking across 16 large language models on a comprehensive real-world emergency department triage data setSemantic proximity Read

Grounded large language models for diagnostic prediction in real-world emergency department settingsSemantic proximity Read

Scalable screening for emergency department missed opportunities for diagnosis using sequential eTriggers and large language modelsSemantic proximity Read

Artificial Intelligence - Large Language Models (LLMs) and Agentic AI in Clinical Decision Support in Outpatient, General Practice and Acute Settings: A Systematic Review of Diagnostic Accuracy, Comparative Efficacy, Clinical Outcomes and Implementation FactorsSemantic proximity Read

A Systematic Review of Large Language Models in Medical Specialties: Applications, Challenges and Future DirectionsSemantic proximity Read

Cross-Model Variability in Large Language Model Triage Behavior for Potential Stroke SymptomsSemantic proximity Read

Assessing the Limitations of Large Language Models in Clinical Practice Guideline-concordant Treatment Decision-making on Real-world DataSemantic proximity Read

MTS-Bench: A Manchester Triage System Benchmark for Language Model Triage SafetySemantic proximity Read

Evaluation of four large language models on complex, infectious disease case scenariosSemantic proximity Read

Large-Language-Model Mortality Risk Stratification in the Intensive Care Unit: A Benchmark Against APACHE IISemantic proximity Read

High Consistency, Limited Accuracy: Evaluating Large Language Models for Binary Medical DiagnosisSemantic proximity Read

Large language models for automatable real-world performance monitoring of diagnostic decision support systems: a comparison to manual doctor panel review in a prospective clinical studySemantic proximity Read