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Enhancing Patient Safety in Prehospital Environment: Analyzing Patient Perspectives on Non-Transport Decisions With Natural Language Processing and Machine Learning.

Hassan FarhatGuillaume AlinierReem TluliMontaha ChakifFatma Babay Ep RekikMa Cleo AlcantaraPadarath GangaramKawther El AifaAhmed MakhloufIan HowlandMohamed Chaker KhenissiSailesh ChauhanCyrine AbidNicholas CastleLoua Al ShaikhMoncef KhadhraouiImed GargouriJames Laughton
Published in: Journal of patient safety (2024)
This study highlighted the utility of Natural Language Processing and ML in enhancing our understanding of patient behaviors and sentiments in prehospital settings. These advanced computational methodologies allowed for a nuanced exploration of patient demographics and sentiments, providing insights for Quality Improvement initiatives. The study also advocates for continuously integrating automated feedback mechanisms to improve patient-centered care in the prehospital context. Continuous integration of automated feedback systems is recommended to improve prehospital patient-centered care.
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