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Related Experiment Video

Updated: Jan 6, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Accuracy of Artificial Intelligence vs Professionally Translated Discharge Instructions.

Melissa Martos¹, Blanca Fields², Samuel G Finlayson¹

¹University of Washington, Seattle.

JAMA Network Open

|September 17, 2025

Summary

Artificial intelligence (AI) translation of pediatric discharge instructions was less accurate than professional human translation for Chinese, Somali, and Vietnamese languages. Spanish AI translations showed similar adequacy and error severity but lower fluency and meaning compared to professional translations.

Related Experiment Videos

Last Updated: Jan 6, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Area of Science:

Medical Informatics
Health Services Research
Clinical Translation

Background:

Patients with limited English proficiency face significant barriers to accessing translated health information, potentially leading to poorer health outcomes.
Artificial intelligence (AI) offers a potential solution for improving access to translated clinical materials, but its accuracy in routine practice needs evaluation.

Purpose of the Study:

To compare the accuracy and quality of AI-generated translations versus professional human translations for pediatric inpatient discharge instructions.

Main Methods:

A comparative effectiveness analysis evaluated AI (Azure) and professional human translations of pediatric discharge instructions in Simplified Chinese, Somali, Spanish, and Vietnamese.
Two professional translators assessed translations for fluency, adequacy, meaning, and error severity on a 5-point scale, blinded to the translation source.

Main Results:

AI translations were generally inferior to professional translations across all tested languages, with lower scores for fluency, adequacy, and meaning.
Spanish AI translations were non-inferior in adequacy and error severity but inferior in fluency and meaning compared to professional translations.
AI translations for Chinese, Vietnamese, and Somali languages demonstrated inferiority across all evaluated metrics, with Somali showing the most significant differences.

Conclusions:

AI translation of discharge instructions performed comparably to professional translation for Spanish but was worse for Chinese, Somali, and Vietnamese.
Implementing AI-based translation requires careful consideration of languages with lesser diffusion to avoid exacerbating health inequities.