Scientific article
Open access

Automatic Classification of Discharge Letters to Detect Adverse Drug Reactions

Published inStudies in Health Technology and Informatics, vol. 270, p. 48-52
Publication date2020

Adverse drug reactions (ADRs) are frequent and associated to significant morbidity, mortality and costs. Therefore, their early detection in the hospital context is vital. Automatic tools could be developed taking into account structured and textual data. In this paper, we present the methodology followed for the manual annotation and automatic classification of discharge letters from a tertiary hospital. The results show that ADRs and causal drugs are explicitly mentioned in the discharge letters and that machine learning algorithms are efficient for the automatic detection of documents containing mentions of ADRs.

  • Adverse Drug Reaction Reporting Systems
  • Algorithms
  • Drug-Related Side Effects and Adverse Reactions
  • Humans
  • Patient Discharge
  • Pharmacovigilance
Citation (ISO format)
FOUFI, Vasiliki et al. Automatic Classification of Discharge Letters to Detect Adverse Drug Reactions. In: Studies in Health Technology and Informatics, 2020, vol. 270, p. 48–52. doi: 10.3233/SHTI200120
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Article (Published version)
ISSN of the journal0926-9630

Technical informations

Creation10/09/2020 5:48:00 PM
First validation10/09/2020 5:48:00 PM
Update time03/15/2023 11:44:59 PM
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