title: Automatic identification and normalization of dosage forms in drug monographs.
abstract: BACKGROUND
  Each day, millions of health consumers seek drug-related information on the Web. Despite some efforts in linking related resources, drug information is largely scattered in a wide variety of websites of different quality and credibility.
  
  
  METHODS
  As a step toward providing users with integrated access to multiple trustworthy drug resources, we aim to develop a method capable of identifying drug's dosage form information in addition to drug name recognition. We developed rules and patterns for identifying dosage forms from different sections of full-text drug monographs, and subsequently normalized them to standardized RxNorm dosage forms.
  
  
  RESULTS
  Our method represents a significant improvement compared with a baseline lookup approach, achieving overall macro-averaged Precision of 80%, Recall of 98%, and F-Measure of 85%.
  
  
  CONCLUSIONS
  We successfully developed an automatic approach for drug dosage form identification, which is critical for building links between different drug-related resources.
authors.affiliation: National Library of Medicine, Bethesda, MD 20894, USA.
authors.forename: Jiao
authors.initials: J
authors.lastname: Li
authors.forename: Zhiyong
authors.initials: Z
authors.lastname: Lu
mesh_terms: D054796:Drug Dosage Calculations; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000378:metabolism
chemical_list: D004364:Pharmaceutical Preparations