COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization

The COVID-19 global pandemic has resulted in international efforts to understand, track, and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related publications across scientific disciplines. Throughout 2020, over 400,000 coronavirus-related publications have been col...

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Detalles Bibliográficos
Autores principales: Esteva, Andre, Kale, Anuprit, Paulus, Romain, Hashimoto, Kazuma, Yin, Wenpeng, Radev, Dragomir, Socher, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041998/
https://www.ncbi.nlm.nih.gov/pubmed/33846532
http://dx.doi.org/10.1038/s41746-021-00437-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041998/
https://www.ncbi.nlm.nih.gov/pubmed/33846532
http://dx.doi.org/10.1038/s41746-021-00437-0

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