Evaluating Large Language Model‐Assisted Emergency Triage: A Comparison of Acuity Assessments by <scp>GPT</scp>‐4 and Medical Experts

Authors

Amit Shaham (ORCID: https://orcid.org/0000-0002-2899-1665)
B Eisenman
Mor Saban (ORCID: https://orcid.org/0000-0001-6869-0907)
Eyal Klang (ORCID: https://orcid.org/0000-0002-4567-3108)
Gal Ben Haim
Yiftach Barash (ORCID: https://orcid.org/0000-0002-7242-1328)
Livnat Burshtein
David Cirulnik
Orly Mymon

Institutions

Tel Aviv University (IL)
Sheba Medical Center (IL)
Icahn School of Medicine at Mount Sinai (US)

Publication Details

Journal: Journal of Clinical Nursing
Published: 2024-11-28
DOI: https://doi.org/10.1111/jocn.17490
Citations: 10
Primary Topic: Emergency and Acute Care Studies
Type: article
Field-Weighted Citation Impact: 6.91

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article

Evaluating Large Language Model‐Assisted Emergency Triage: A Comparison of Acuity Assessments by GPT‐4 and Medical Experts

Amit Shaham, B Eisenman, Mor Saban, Eyal Klang et al.

Nov 28, 2024

10 citations

Journal of Clinical Nursing

Emergency and Acute Care Studies

6.91

article

Evaluating Large Language Model‐Assisted Emergency Triage: A Comparison of Acuity Assessments by GPT‐4 and Medical Experts

Amit Shaham, B Eisenman, Mor Saban, Eyal Klang, Gal Ben Haim, Yiftach Barash, Livnat Burshtein, David Cirulnik, Orly Mymon

November 28, 2024article en

10 citations

Abstract

No abstract available for this paper.

Journal of Clinical Nursing

Tel Aviv University (IL), Sheba Medical Center (IL), Icahn School of Medicine at Mount Sinai (US)

Peace, Justice and strong institutions

Openalex Percentile: Top 3%

Emergency and Acute Care Studies

6.91

DOI Open Access PDF OpenAlex

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Evaluating Large Language Model‐Assisted Emergency Triage: A Comparison of Acuity Assessments by <scp>GPT</scp>‐4 and Medical Experts — Amit Shaham, B Eisenman, et al. · Journal of Clinical Nursing (2024) | TGRS Research Map | TGRS