DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction.
artificial intelligence
deep learning
drug indication
natural language processing
transformers
Journal
Frontiers in artificial intelligence
ISSN: 2624-8212
Titre abrégé: Front Artif Intell
Pays: Switzerland
ID NLM: 101770551
Informations de publication
Date de publication:
2021
2021
Historique:
received:
18
05
2021
accepted:
19
07
2021
entrez:
19
8
2021
pubmed:
20
8
2021
medline:
20
8
2021
Statut:
epublish
Résumé
Drug labeling contains an 'INDICATIONS AND USAGE' that provides vital information to support clinical decision making and regulatory management. Effective extraction of drug indication information from free-text based resources could facilitate drug repositioning projects and help collect real-world evidence in support of secondary use of approved medicines. To enable AI-powered language models for the extraction of drug indication information, we used manual reading and curation to develop a
Identifiants
pubmed: 34409286
doi: 10.3389/frai.2021.711467
pii: 711467
pmc: PMC8366025
doi:
Types de publication
Journal Article
Langues
eng
Pagination
711467Informations de copyright
Copyright © 2021 Bhatt, Roberts, Chen, Li, Connor, Hatim, Mikailov, Tong and Liu.
Déclaration de conflit d'intérêts
RR is co-founder and co-director of ApconiX, an integrated toxicology and ion channel company that provides expert advice on non-clinical aspects of drug discovery and drug development to academia, industry, and not-for-profit organizations. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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