Drug Name Recognition and Classification in Biomedical Texts: A Case Study Outlining Approaches Underpinning Automated Systems Articles uri icon

publication date

  • September 2008

start page

  • 816

end page

  • 823

issue

  • 17-18

volume

  • 13

International Standard Serial Number (ISSN)

  • 1359-6446

Electronic International Standard Serial Number (EISSN)

  • 1878-5832

abstract

  • This article presents a system for drug name recognition and classification inbiomedical texts. The system combines information obtained by the Unified Medical Language System (UMLS) MetaMap Transfer (MMTx) program and nomenclature rules recommended by the World Health Organization (WHO) International Nonproprietary Names (INNs) Program to identify and classify pharmaceutical substances. Moreover, the system is able to detect possible candidates for drug names that have not been detected by MMTx program by applying these rules, achieving, in this way, a broader coverage. This work is the first step in a method for automatic detection of drug interactions from biomedical texts, a specific type of adverse drug event of special interest in patient safety.