Artificial Intelligence (AI) in Action: Addressing the COVID-19 Pandemic with Natural Language Processing (NLP)
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Abstract (arXiv)
The COVID-19 pandemic has had a significant impact on society, both because of the serious health effects of COVID-19 and because of public health measures implemented to slow its spread. Many of these difficulties are fundamentally information needs; attempts to address these needs have caused an information overload for both researchers and the public. Natural language processing (NLP), the branch of artificial intelligence that interprets human language, can be applied to address many of the information needs made urgent by the COVID-19 pandemic. This review surveys approximately 150 NLP studies and more than 50 systems and datasets addressing the COVID-19 pandemic. We detail work on four core NLP tasks: information retrieval, named entity recognition, literature-based discovery, and question answering. We also describe work that directly addresses aspects of the pandemic through four additional tasks: topic modeling, sentiment and emotion analysis, caseload forecasting, and misinformation detection. We conclude by discussing observable trends and remaining challenges.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Oct 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2.
5 papers.
- 2021Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Reviewcited by 35
- 2022Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotationscited by 14
- 2023Bioformer: an efficient transformer language model for biomedical text miningcited by 9
- 2022LitMC-BERT: transformer-based multi-label classification of biomedical literature with an application on COVID-19 literature curationcited by 6
- 2023Covidia: COVID-19 Interdisciplinary Academic Knowledge Graphcited by 0
- 2023Covidia: COVID-19 Interdisciplinary Academic Knowledge Graph14 Apr 2023
- 2023Bioformer: an efficient transformer language model for biomedical text mining3 Feb 2023
- 2022Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations20 Apr 2022
- 2022LitMC-BERT: transformer-based multi-label classification of biomedical literature with an application on COVID-19 literature curation19 Apr 2022
- 2021Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review7 Jul 2021