Artificial Intelligence (AI) in Action: Addressing the COVID-19 Pandemic with Natural Language Processing (NLP)
arXiv:2010.16413 · doi:10.1146/annurev-biodatasci-021821-061045
Abstract
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.
51 pages, 3 figures and 2 tables; published at the Annual Review of Biomedical Data Science
References in corpus (9)
- BioBERT: a pre-trained biomedical language representation model for biomedical text mining
- COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification
- Using Reports of Own and Others' Symptoms and Diagnosis on Social Media to Predict COVID-19 Case Counts: Observational Infoveillance Study in Mainland China
- India nudges to contain COVID-19 pandemic: a reactive public policy analysis using machine-learning based topic modelling
- COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
- Ontology-driven weak supervision for clinical entity classification in electronic health records
- COVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model
- Examination of Community Sentiment Dynamics due to COVID-19 Pandemic: A Case Study from A State in Australia
- COVID-19 therapy target discovery with context-aware literature mining