ArticleAnnals of nuclear medicine2025
Can interactive artificial intelligence be used for patient explanations of nuclear medicine examinations in Japanese?
Article in Annals of nuclear medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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Who cites it
1 citing paper in PubMed.
- Real-world evaluation of large language model for patients medical and administrative queries in nuclear medicine.NPJ digital medicine · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to evaluate the accuracy and validity of patient explanations about nuclear medicine examinations generated in Japanese using ChatGPT- 3.5 and ChatGPT- 4.
methodsChatGPT was used to generate Japanese language explanations for seven single-photon emission computed tomography examinations (bone scintigraphy, brain perfusion imaging, myocardial perfusion imaging, dopamine transporter scintigraphy [DAT scintigraphy], sentinel lymph node scintigraphy, lung perfusion scintigraphy, and renal function scintigraphy) and
resultsChatGPT- 4 demonstrated significantly higher accuracy and validity than ChatGPT- 3.5, with 77.9% of responses rated as above average or excellent for accuracy, in comparison to 36.3% for ChatGPT- 3.5. For validity, 73.1% of ChatGPT- 4's responses were rated as above average or excellent, in comparison to 19.6% for ChatGPT- 3.5. ChatGPT- 4 outperformed ChatGPT- 3.5 in all examinations, with notable improvements in bone scintigraphy, lung perfusion scintigraphy, and DAT scintigraphy.
conclusionThese findings suggest that ChatGPT- 4 can be a valuable tool for providing patient explanations of nuclear medicine examinations. However, its application still requires expert supervision, and further research is needed to address potential risks and security concerns.
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Registered trials
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.