Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Medical Education

Date Submitted: Dec 20, 2024
Date Accepted: Jan 27, 2025

The final, peer-reviewed published version of this preprint can be found here:

Enhancing AI-Driven Medical Translations: Considerations for Language Concordance

Quon S, Zhou S

Enhancing AI-Driven Medical Translations: Considerations for Language Concordance

JMIR Med Educ 2025;11:e70420

DOI: 10.2196/70420

PMID: 40215956

PMCID: 12039939

Comment on “ChatGPT May Improve Access to Language-Concordant Care for Patients With Non–English Language Preferences”

  • Stephanie Quon; 
  • Sarah Zhou

ABSTRACT

The study by Dzuali and Seiger et al. explores the use of ChatGPT for translating patient education materials into multiple languages, highlighting its potential to bridge gaps in language-concordant care. While the research successfully demonstrates ChatGPT’s ability to provide clinically usable translations for Spanish and Russian, its performance with Mandarin is notably suboptimal due to linguistic complexities, such as nuanced sentence structures and specialized terminology. This raises important considerations for refining AI translation approaches, particularly for languages like Mandarin, where cultural context and grammar intricacies significantly impact translation accuracy. Additionally, the study's reliance on post-translation review by board-certified dermatologists could be enhanced by incorporating a wider range of human oversight, including linguistic experts and specialists in medical translation. Future research should explore the use of alternative prompts and varying levels of human intervention to improve translation quality and ensure culturally appropriate, clinically relevant translations across diverse languages. This work contributes valuable insights into the evolving field of AI-assisted medical translation and highlights areas for further development and validation.


 Citation

Please cite as:

Quon S, Zhou S

Enhancing AI-Driven Medical Translations: Considerations for Language Concordance

JMIR Med Educ 2025;11:e70420

DOI: 10.2196/70420

PMID: 40215956

PMCID: 12039939

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.