Evidence map›Paper›PMID 40220179›Full record

ArticleEuropean archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery2025

AI in clinical decision-making: ChatGPT-4 vs. Llama2 for otolaryngology cases.

Antonino Maniaci, Cosima C Hoch, Lise Sogalow, Benedikt Schmidl, Jerome R Lechien

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Comparative evaluation of four large language models (ChatGPT-5, Gemini 2.5 Pro, Claude Sonnet-4, and DeepSeek-R1) for diagnostic and therapeutic decision-making in real-world otolaryngology scenarios.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Antonino ManiaciDepartment of Medical and Surgical Sciences, Faculty of Medicine, University of Enna Kore, Enna, Italy. Antonino.maniaci@unikore.it.ORCID http://orcid.org/0000-0002-1251-0185
Cosima C HochYoifos Research Committee, Paris, France.
Lise SogalowYoifos Research Committee, Paris, France.
Benedikt SchmidlDepartment of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich (TUM), 81675, Munich, Germany.
Jerome R LechienYoifos Research Committee, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the diagnostic accuracy, appropriateness of additional examination recommendations, and consistency of therapeutic regimens by ChatGPT-4 and Llama2 based on real otolaryngology cases.

methodsA prospective controlled study was conducted on 98 anonymized otolaryngology cases. Clinical information was entered in ChatGPT-4 and Llama2 for reaching primary diagnoses, additional examination recommendations, and treatment strategies. Two independent otolaryngologists evaluated the AI outputs using the artificial intelligence performance instrument (AIPI), evaluating diagnostic accuracy, appropriateness of examination, and adequacy of treatment. Statistical comparisons were conducted between the AI systems and expert decisions. Interrater reliability was evaluated with kappa statistics.

resultsChatGPT-4 diagnosed 82% correctly, outperforming Llama2 at 76%. For additional examinations, ChatGPT-4 suggested relevant and appropriate tests in 88% of the studies, while Llama2 did so in 83%. Treatment appropriateness was achieved in 80% of the cases through ChatGPT-4 and 72% through Llama2. Sometimes, both systems suggested inappropriate tests. The interrater reliability was high for AIPI scores (kappa = 0.85).

conclusionChatGPT-4 and Llama2 have shown great potential as clinical decision-support tools in otolaryngology, with ChatGPT-4 exhibiting superior performance. At the same time, non-relevant recommendations indicate further refinement and human oversight to ensure safe application in clinical practice.

Indexed as

Artificial IntelligenceClinical Decision-MakingOtolaryngologyAdultAgedFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedProspective StudiesReproducibility of ResultsAIArtificial intelligenceChatGPT-4Clinical decision makingLama2

Identifiers

PMID40220179

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.