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Clinical Relevance of Pharmacist Intervention: Development of a Named Entity Recognition Model on Unstructured Comments

Abstract : We developed a clinical named entity recognition model to predict clinical relevance of pharmacist interventions (PIs) by identifying and labelling expressions from unstructured comments of PIs. Three labels, drug, kidney and dosage, had a great inter-annotator agreement (>60%) and could be used as reference labelization. These labels also showed a high precision (>70%) and a variable recall (50–90 %).
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https://hal.univ-reims.fr/hal-03591786
Contributor : Marius Colin Connect in order to contact the contributor
Submitted on : Monday, February 28, 2022 - 6:34:05 PM
Last modification on : Tuesday, March 1, 2022 - 3:30:33 AM

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Justine Clarenne, Sonia Priou, Aymeric Alixe, Olivier Martin, Céline Mongaret, et al.. Clinical Relevance of Pharmacist Intervention: Development of a Named Entity Recognition Model on Unstructured Comments. Public Health and Informatics, IOS Press, 2021, Studies in Health Technology and Informatics, ⟨10.3233/SHTI210210⟩. ⟨hal-03591786⟩

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