Evaluating large language models for specialist referral triage in primary care: a quantitative study using otolaryngology scenarios

AI decision support tools show potential to assist specialist referral triage in primary care. Clear, structured input is essential to maximize safety and reliability.

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Publication Details

Journal
Family Practice
Published
2025-10-21
DOI
https://doi.org/10.1093/fampra/cmaf087
Citations
3
Primary Topic
Healthcare Systems and Technology
Type
article
Field-Weighted Citation Impact
8.29
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article

Evaluating large language models for specialist referral triage in primary care: a quantitative study using otolaryngology scenarios

Ben Gvili, David Shahal, Eran Glikson, David Yogev et al.
3 citations
Family Practice
Healthcare Systems and Technology
8.29
article

Evaluating large language models for specialist referral triage in primary care: a quantitative study using otolaryngology scenarios

Ben Gvili, David Shahal, Eran Glikson, David Yogev, Shibli Alsleibi, Sholem Hack, Rebecca Attal
article en
3 citations

Abstract

AI decision support tools show potential to assist specialist referral triage in primary care. Clear, structured input is essential to maximize safety and reliability.

Family PracticeVol. 42(6)
Tel Aviv University (IL), University of Nicosia (CY), Sheba Medical Center (IL)
Openalex Percentile: Top 3%
Healthcare Systems and Technology
8.29
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