PMID- 27577400
OWN - NLM
STAT- MEDLINE
DCOM- 20170428
LR  - 20170428
IS  - 1879-8365 (Electronic)
IS  - 0926-9630 (Linking)
VI  - 228
DP  - 2016
TI  - Automatic Extraction of Drug Adverse Effects from Product Characteristics (SPCs): 
      A Text Versus Table Comparison.
PG  - 339-43
AB  - BACKGROUND: Potential adverse effects (AEs) of drugs are described in their 
      summary of product characteristics (SPCs), a textual document. Automatic 
      extraction of AEs from SPCs is useful for detecting AEs and for building drug 
      databases. However, this task is difficult because each AE is associated with a 
      frequency that must be extracted and the presentation of AEs in SPCs is 
      heterogeneous, consisting of plain text and tables in many different formats. 
      METHODS: We propose a taxonomy for the presentation of AEs in SPCs. We set up 
      natural language processing (NLP) and table parsing methods for extracting AEs 
      from texts and tables of any format, and evaluate them on 10 SPCs. RESULTS: 
      Automatic extraction performed better on tables than on texts. CONCLUSION: Tables 
      should be recommended for the presentation of the AEs section of the SPCs.
FAU - Lamy, Jean-Baptiste
AU  - Lamy JB
AD  - LIMICS, Universite Paris 13, Sorbonne Paris Cite, 93017 Bobigny, France, INSERM 
      UMRS 1142, UPMC Universite Paris 6, Sorbonne Universites, Paris.
FAU - Ugon, Adrien
AU  - Ugon A
AD  - LIMICS, Universite Paris 13, Sorbonne Paris Cite, 93017 Bobigny, France, INSERM 
      UMRS 1142, UPMC Universite Paris 6, Sorbonne Universites, Paris.
FAU - Berthelot, Helene
AU  - Berthelot H
AD  - LIMICS, Universite Paris 13, Sorbonne Paris Cite, 93017 Bobigny, France, INSERM 
      UMRS 1142, UPMC Universite Paris 6, Sorbonne Universites, Paris.
LA  - eng
PT  - Comparative Study
PT  - Journal Article
PL  - Netherlands
TA  - Stud Health Technol Inform
JT  - Studies in health technology and informatics
JID - 9214582
MH  - *Automation
MH  - *Drug-Related Side Effects and Adverse Reactions
MH  - Humans
MH  - *Information Storage and Retrieval
MH  - Natural Language Processing
MH  - Product Surveillance, Postmarketing
MH  - Software
EDAT- 2016/09/01 06:00
MHDA- 2017/04/30 06:00
CRDT- 2016/09/01 06:00
PHST- 2016/09/01 06:00 [entrez]
PHST- 2016/09/01 06:00 [pubmed]
PHST- 2017/04/30 06:00 [medline]
PST - ppublish
SO  - Stud Health Technol Inform. 2016;228:339-43.