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Evaluating the Performance of AI Large Language Models in Detecting Pediatric Medication Errors Across Languages: A

Rana K Abu-Farha1, Haneen Abuzaid2, Jena Alalawneh3

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Summary

Microsoft Copilot showed the highest accuracy in detecting pediatric medication errors among four AI models. Performance varied by language, with Arabic generally showing lower accuracy, highlighting the need for better multilingual AI training.

Keywords:
AI modelsaccuracymedication errorspediatricsreproducibilitysensitivityspecificity

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Area of Science:

  • Artificial Intelligence in Healthcare
  • Pharmacovigilance
  • Pediatric Drug Safety

Background:

  • Medication errors pose a significant risk in pediatric pharmacotherapy.
  • Evaluating the efficacy of artificial intelligence (AI) tools for medication error detection is crucial.

Purpose of the Study:

  • To assess the performance of four AI models (GPT-5, GPT-4, Microsoft Copilot, Google Gemini) in identifying medication errors in pediatric case scenarios.
  • To compare AI model performance across English and Arabic languages.

Main Methods:

  • Sixty pediatric cases, half containing medication errors across four therapeutic systems, were analyzed.
  • AI models were tested using a unified prompt in both English and Arabic.
  • Performance metrics included accuracy, sensitivity, specificity, and reproducibility, analyzed using SPSS version 22.

Main Results:

  • Microsoft Copilot achieved the highest accuracy (86.7% English, 85.0% Arabic), followed by GPT-5.
  • Google Gemini exhibited the lowest accuracy (76.7% English, 73.3% Arabic).
  • Arabic language performance was generally lower than English; Microsoft Copilot demonstrated superior reproducibility and inter-language agreement.

Conclusions:

  • Microsoft Copilot outperformed other AI models in detecting pediatric medication errors in this study.
  • The findings underscore the need for enhanced multilingual AI training to ensure equitable performance across languages.
  • Human oversight and domain-specific AI training are vital for safe application in pediatric pharmacotherapy.