Evidence map›Paper›PMID 41761593›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2026

Do Large Language Models Perform Equally Across Languages? A Comparison of Responses to Frequently Asked Questions in Anesthesiology.

Hadi Ufuk Yörükoğlu, Can Aksu, Pervez Sultan, Serkan Tulgar

Abstract readComparative Study
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hadi Ufuk YörükoğluDepartment of Anesthesiology and Reanimation, Kocaeli University School of Medicine, Kocaeli, Turkey.
Can AksuDepartment of Anesthesiology and Reanimation, University School of Medicine, Kocaeli, Turkey.
Pervez SultanDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Serkan TulgarDepartment of Anesthesiology and Reanimation, Faculty of Medicine, Göztepe Medical Park Hospital, Bahçeşehir University, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND With the increasing use of large language model (LLM) chatbots in healthcare, evaluating their ability to provide reliable and understandable information in multiple languages is critical, particularly in fields such as anesthesia, where patient education is essential. The study primarily aimed to compare the quality of ChatGPT 4.0's and DeepSeek V3's English responses, with secondary aims to evaluate content and communication differences between English and Turkish responses. MATERIAL AND METHODS Anesthesiologists proficient in both languages were recruited as experts. Ten frequently asked questions in anesthesia were selected and translated for evaluation. Responses from ChatGPT 4.0 and DeepSeek V3 in both English and Turkish were assessed for overall quality and content quality (accuracy, comprehensiveness, and safety) and communication quality (understanding, empathy/tone, and ethics), and Turkish and English responses were compared by the evaluators. RESULTS Eleven experts evaluated the responses. English responses of ChatGPT 4.0 were superior to the English responses of DeepSeek V3 in overall (P<0.001). English responses of ChatGPT 4.0 were superior to the Turkish responses in the terms of overall, content, and communication quality (P<0.001 each) and English responses of DeepSeek V3 were superior to the Turkish responses in the terms of overall (P<0.001), content (P<0.001) and communication (P=0.001) quality. CONCLUSIONS ChatGPT 4.0 performed better than DeepSeek V3 in the English language in terms of overall quality of responses to 10 frequently asked questions in the field of anesthesia and the English responses provided by ChatGPT 4.0 and DeepSeek V3 outperformed the Turkish responses.

Indexed as

AnesthesiologyLanguageCommunicationHumansLarge Language ModelsSurveys and QuestionnairesTurkey

Identifiers

PMID41761593
PMCPMC12958780

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.