The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges
The COVID-19 pandemic is the most devastating public health crisis in at least a century and has affected the lives of billions of people worldwide in unprecedented ways. Compared to pandemics of this scale in the past, societies are now equipped with advanced technologies that can mitigate the impa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/10/11/2270 |
| _version_ | 1797465250964963328 |
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| author | Mohammed Ali Al-Garadi Yuan-Chi Yang Abeed Sarker |
| author_facet | Mohammed Ali Al-Garadi Yuan-Chi Yang Abeed Sarker |
| author_sort | Mohammed Ali Al-Garadi |
| collection | DOAJ |
| description | The COVID-19 pandemic is the most devastating public health crisis in at least a century and has affected the lives of billions of people worldwide in unprecedented ways. Compared to pandemics of this scale in the past, societies are now equipped with advanced technologies that can mitigate the impacts of pandemics if utilized appropriately. However, opportunities are currently not fully utilized, particularly at the intersection of data science and health. Health-related big data and technological advances have the potential to significantly aid the fight against such pandemics, including the current pandemic’s ongoing and long-term impacts. Specifically, the field of natural language processing (NLP) has enormous potential at a time when vast amounts of text-based data are continuously generated from a multitude of sources, such as health/hospital systems, published medical literature, and social media. Effectively mitigating the impacts of the pandemic requires tackling challenges associated with the application and deployment of NLP systems. In this paper, we review the applications of NLP to address diverse aspects of the COVID-19 pandemic. We outline key NLP-related advances on a chosen set of topics reported in the literature and discuss the opportunities and challenges associated with applying NLP during the current pandemic and future ones. These opportunities and challenges can guide future research aimed at improving the current health and social response systems and pandemic preparedness. |
| first_indexed | 2024-03-09T18:18:53Z |
| format | Article |
| id | doaj.art-a692a3409c6844139ca15e51f01b0956 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-09T18:18:53Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-a692a3409c6844139ca15e51f01b09562023-11-24T08:27:54ZengMDPI AGHealthcare2227-90322022-11-011011227010.3390/healthcare10112270The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and ChallengesMohammed Ali Al-Garadi0Yuan-Chi Yang1Abeed Sarker2Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37240, USADepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USADepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USAThe COVID-19 pandemic is the most devastating public health crisis in at least a century and has affected the lives of billions of people worldwide in unprecedented ways. Compared to pandemics of this scale in the past, societies are now equipped with advanced technologies that can mitigate the impacts of pandemics if utilized appropriately. However, opportunities are currently not fully utilized, particularly at the intersection of data science and health. Health-related big data and technological advances have the potential to significantly aid the fight against such pandemics, including the current pandemic’s ongoing and long-term impacts. Specifically, the field of natural language processing (NLP) has enormous potential at a time when vast amounts of text-based data are continuously generated from a multitude of sources, such as health/hospital systems, published medical literature, and social media. Effectively mitigating the impacts of the pandemic requires tackling challenges associated with the application and deployment of NLP systems. In this paper, we review the applications of NLP to address diverse aspects of the COVID-19 pandemic. We outline key NLP-related advances on a chosen set of topics reported in the literature and discuss the opportunities and challenges associated with applying NLP during the current pandemic and future ones. These opportunities and challenges can guide future research aimed at improving the current health and social response systems and pandemic preparedness.https://www.mdpi.com/2227-9032/10/11/2270COVID-19natural language processinghealth applicationsmachine learningdeep learning |
| spellingShingle | Mohammed Ali Al-Garadi Yuan-Chi Yang Abeed Sarker The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges Healthcare COVID-19 natural language processing health applications machine learning deep learning |
| title | The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges |
| title_full | The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges |
| title_fullStr | The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges |
| title_full_unstemmed | The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges |
| title_short | The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges |
| title_sort | role of natural language processing during the covid 19 pandemic health applications opportunities and challenges |
| topic | COVID-19 natural language processing health applications machine learning deep learning |
| url | https://www.mdpi.com/2227-9032/10/11/2270 |
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