@inproceedings{zecevic-etal-2024-simplification,
    title = "On Simplification of Discharge Summaries in {S}erbian: Facing the Challenges",
    author = "Ze{\v{c}}evi{\'c}, An{\dj}elka  and
      {\'C}ulafi{\'c}, Milica  and
      Stojkovi{\'c}, Stefan",
    editor = "Demner-Fushman, Dina  and
      Ananiadou, Sophia  and
      Thompson, Paul  and
      Ondov, Brian",
    booktitle = "Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.cl4health-1.12/",
    pages = "104--108",
    abstract = "The simplified information page (SIP) is a simplified discharge summary created to mitigate health risks caused by low medical comprehension. One of the most critical aspects of medical comprehension concerns interpreting medication instructions such as proper dosing, frequency, and duration. In our work, we examine the capacities of mainstream Large Language Models (LLMs) such as ChatGPT and Gemini to generate SIP-like medication-oriented pages based on the provided discharge summaries. We are sharing the initial qualitative assessments of our study based on a small collection of discharge summaries in Serbian, pointing to noticed inaccuracies, unfaithful content, and language quality. Hopefully, these findings might be helpful in addressing the multilingual perspective of patient-oriented language."
}