ArticleJapanese journal of radiology2025
Response accuracy of GPT-4 across languages: insights from an expert-level diagnostic radiology examination in Japan.
Article in Japanese journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating the Performance of ChatGPT on Board-Style Examination Questions in Ophthalmology: A Meta-Analysis.Journal of medical systems · 2025Pooled it
- Multimodal Large Language Models for Dental Chart Image Interpretation: Cross-Sectional Benchmarking Study With Students and Clinicians.JMIR medical education · 2026Article
- Percutaneous thermal ablation for renal cell carcinoma: a comprehensive review of current evidence and future directions.La Radiologia medica · 2026Review
- AI-Generated Versus Human Supervisor Feedback on Medical Students' Clinical Clerkship Logs: Cross-Sectional Convergent Mixed Methods Study.JMIR medical education · 2026Article
- Feasibility of retrieval-augmented generation for large language models with Japanese input in radiotherapy.Journal of radiation research · 2026Article
- Insufficient reporting quality in large language model studies in the field of radiology.Insights into imaging · 2026Article
- Dermatology "AI Babylon": Cross-Language Evaluation of AI-Crafted Dermatology Descriptions.Medicina (Kaunas, Lithuania) · 2026Article
- Role of Artificial Intelligence in Surgical Training by Assessing GPT-4 and GPT-4o on the Japan Surgical Board Examination With Text-Only and Image-Accompanied Questions: Performance Evaluation Study.JMIR medical education · 2025Article
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8 authors.
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Abstract
purposeThis study aims to investigate the effects of language selection and translation quality on Generative Pre-trained Transformer-4 (GPT-4)'s response accuracy to expert-level diagnostic radiology questions. MATERIALS AND
methodsWe analyzed 146 diagnostic radiology questions from the Japan Radiology Board Examination (2020-2022), with consensus answers provided by two board-certified radiologists. The questions, originally in Japanese, were translated into English by GPT-4 and DeepL and into German and Chinese by GPT-4. Responses were generated by GPT-4 five times per question set per language. Response accuracy was compared between languages using one-way ANOVA with Bonferroni correction or the Mann-Whitney U test. Scores on selected English questions translated by a professional service and GPT-4 were also compared. The impact of translation quality on GPT-4's performance was assessed by linear regression analysis.
resultsThe median scores (interquartile range) for the 146 questions were 70 (68-72) (Japanese), 89 (84.5-95.5) (GPT-4 English), 64 (55.5-67) (Chinese), and 56 (46.5-67.5) (German). Significant differences were found between Japanese and English (p = 0.002) and between Japanese and German (p = 0.022). The counts of correct responses across five attempts for each question were significantly associated with the quality of translation into English (GPT-4, DeepL) and German (GPT-4). In a subset of 31 questions where English translations yielded fewer correct responses than Japanese originals, professionally translated questions yielded better scores than those translated by GPT-4 (13 versus 8 points, p = 0.0079).
conclusionGPT-4 exhibits higher accuracy when responding to English-translated questions compared to original Japanese questions, a trend not observed with German or Chinese translations. Accuracy improves with higher-quality English translations, underscoring the importance of high-quality translations in improving GPT-4's response accuracy to diagnostic radiology questions in non-English languages and aiding non-native English speakers in obtaining accurate answers from large language models.
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