Identifying tweets of personal health experience through word embedding and LSTM neural network

BACKGROUND: As Twitter has become an active data source for health surveillance research, it is important that efficient and effective methods are developed to identify tweets related to personal health experience. Conventional classification algorithms rely on features engineered by human domain ex...

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Detalles Bibliográficos
Autores principales: Jiang, Keyuan, Feng, Shichao, Song, Qunhao, Calix, Ricardo A., Gupta, Matrika, Bernard, Gordon R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998756/
https://www.ncbi.nlm.nih.gov/pubmed/29897323
http://dx.doi.org/10.1186/s12859-018-2198-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998756/
https://www.ncbi.nlm.nih.gov/pubmed/29897323
http://dx.doi.org/10.1186/s12859-018-2198-y

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