Clinical Relevance of Pharmacist Intervention: Development of a Named Entity Recognition Model on Unstructured Comments
Résumé
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 %).