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

Abstract 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...

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Bibliographic Details
Main Authors: Andre Esteva, Anuprit Kale, Romain Paulus, Kazuma Hashimoto, Wenpeng Yin, Dragomir Radev, Richard Socher
Format: article
Language:EN
Published: Nature Portfolio 2021
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Online Access:https://doaj.org/article/b821725462d6408ea729067c04e6893f
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