Evidence map›Paper›PMID 42315139›Full record

Observational studyJournal of medical Internet research2026

Comparative Evaluation of ChatGPT, Google Translate, and UD Talk for Chinese-to-Japanese Translation in Cardiology and Pulmonology Outpatient Consultations: Prospective Observational Study.

Ke-Yun Chao, Chia-Hui Huang, Wei-Lun Liu, Chao-Yu Chen, Ai Yin Lim, Yi-Zhen Chu, Atsuko Sasaoka, Chung-Yu Lin

Abstract readObservational StudyComparative Study
In one paragraph

Observational study in Journal of medical Internet 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

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ke-Yun ChaoDepartment of Respiratory Therapy, College of Medicine, Fu Jen Catholic University, New Taipei City, Taiwan.ORCID https://orcid.org/0000-0001-5143-6873
Chia-Hui HuangGraduate Institute of Cross-Cultural Studies, Fu Jen Catholic University, New Taipei City, Taiwan.ORCID https://orcid.org/0009-0009-0712-0068
Wei-Lun LiuCenter for Health Research and Innovation, Fu Jen Catholic University, New Taipei City, Taiwan.ORCID https://orcid.org/0000-0001-8593-8492
Chao-Yu ChenDepartment of Life Science, Fu Jen Catholic University, New Taipei City, Taiwan.ORCID https://orcid.org/0009-0008-1812-3857
Ai Yin LimDepartment of Physical Therapy, College of Medical and Health Science, Asia University, Taichung, Taiwan.ORCID https://orcid.org/0000-0002-7647-585X
Yi-Zhen ChuTelehealth Center, Fu Jen Catholic University Hospital, Fu Jen Catholic University, New Taipei City, Taiwan.ORCID https://orcid.org/0009-0000-4114-2011
Atsuko SasaokaGraduate Institute of Cross-Cultural Studies, Fu Jen Catholic University, New Taipei City, Taiwan.ORCID https://orcid.org/0009-0000-4734-0297
Chung-Yu LinDivision of Cardiology, Fu Jen Catholic University Hospital, Fu Jen Catholic University, New Taipei City, Taiwan.ORCID https://orcid.org/0009-0003-1209-3603

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLanguage barriers between health care providers and patients can compromise communication quality, patient safety, and health care equity. When professional interpreter services are limited, particularly in outpatient settings, artificial intelligence-based translation tools may serve as supplementary communication aids.

objectiveThis study compared 3 Chinese-to-Japanese translation tools (ChatGPT, Google Translate, and UD Talk) in terms of their performance in real-world cardiology and pulmonology outpatient consultations.

methodsIn this single-center prospective observational study, audio-recorded outpatient consultations between December 2024 and November 2025 were analyzed. Verbatim physician-patient dialogues were translated using the 3 systems. Selected dialogue exchanges were evaluated by professional medical interpreters for translation accuracy and by Japanese-speaking lay participants for translation satisfaction using a 6-point Likert scale. Similarity of translation outputs was assessed at the dialogue exchange level.

resultsA total of 20 outpatient consultations comprising 2450 dialogue exchanges were analyzed. ChatGPT had significantly higher translation accuracy and satisfaction scores than Google Translate and UD Talk, with median scores of 5.0 (IQR 4.0-5.0) for both outcomes compared with 2.0 (IQR 1.0-3.0) for Google Translate and UD Talk (P<.001), and maintained a consistently high performance in both specialties. Google Translate and UD Talk exhibited substantially higher similarity (2131/2450, 87%) to each other than to ChatGPT in translated outputs (119/2450, 4.9% to 122/2450, 5%, respectively; P<.001).

conclusionsIn Chinese-to-Japanese translations of outpatient medical consultations, ChatGPT demonstrated higher accuracy and user satisfaction than Google Translate and UD Talk. These findings indicate that artificial intelligence-assisted translation may support multilingual clinical communication when used as a complementary aid alongside professional interpreter services.

Indexed as

CardiologyPulmonary MedicineReferral and ConsultationTranslationsAdultArtificial IntelligenceCommunication BarriersEast Asian PeopleFemaleHumansJapanMaleMedical InterpretingMiddle AgedOutpatientsProspective StudiesAIartificial intelligencecardiopulmonary diseaselanguage barriermachine translationmedical communicationmedical interpretation

Identifiers

PMID42315139
PMCPMC13329329

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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.