ArticlePediatric emergency care2025
Artificial Intelligence as a Language Barrier Application in a Simulated Health Care Setting: A Proof-of-Concept Study.
Article in Pediatric emergency care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe evaluated the accuracy of an artificial intelligence program (ChatGPT 4.0) as a medical translation modality in a simulated pediatric urgent care setting.
methodsTwo entirely separate instances of ChatGPT 4.0 were used. The first served as a simulated patient (SP). The SP generated complaints and symptoms while processing and generating text only in Spanish. A human provider (blinded to diagnosis) conducted a clinical "visit" with the SP. The provider typed questions and instructions in English only. A second instance of ChatGPT 4.0 was the artificial medical interpreter (AMI). The AMI translated the provider's questions/instructions from English to Spanish and the SP's responses/concerns from Spanish to English in real time. Post-visit transcripts were then reviewed for errors by a human-certified medical interpreter.
resultsWe conducted 10 simulated visits with 3597 words translated by the AMI (1331 English and 2266 Spanish). There were 23 errors (raw accuracy rate of 99.4%). Errors were categorized as: 9 omissions, 2 additions, 11 substitutions, and 1 editorialization. Three errors were judged to have potential clinical consequences, although these were minor ambiguities, readily resolved by the provider during the visit. Also, the AMI made repeated errors of gender (masculine/feminine) and second person formality ("usted"/"tu"). None of these were judged to have potential clinical consequences.
conclusionsThe AMI accurately and safely translated the written content of simulated urgent care visits. It may serve as the basis for an expedient, cost-effective medical interpreter modality. Further work should seek to couple this translation accuracy with speech recognition and generative technology in trials with actual patients.
Indexed as
Identifiers
What OpenQuestion holds
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.