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Deep learning models in detection of dietary supplement adverse event signals from Twitter
OBJECTIVE: The objective of this study is to develop a deep learning pipeline to detect signals on dietary supplement-related adverse events (DS AEs) from Twitter. MATERIALS AND METHODS: We obtained 247 807 tweets ranging from 2012 to 2018 that mentioned both DS and AE. We designed a tailor-made ann...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8497875/ https://www.ncbi.nlm.nih.gov/pubmed/34632323 http://dx.doi.org/10.1093/jamiaopen/ooab081 |