Annotating Clinical Text using a FHIR-Based Drug Ontology in a Natural Language Processing System Public Deposited

Conclusions: A drug terminology was transformed into FHIR resources, and the same resources were reused as a drug ontology to normalize unstructured medication names and attributes through NLP techniques. Further insight into the performance of MedXN-FHIR in assigning RxNorm identifiers would be useful.

Objectives: To develop a medication natural language processing (NLP) system that was derived from MedXN and to evaluate its performance in annotating medication name, dose, route, frequency, and duration using the 2009 i2b2 Medication Extraction Challenge dataset.

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