Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature With Unsupervised Word Embeddings and Machine Learning: Evidence-Based Study
BackgroundEvidence from peer-reviewed literature is the cornerstone for designing responses to global threats such as COVID-19. In massive and rapidly growing corpuses, such as COVID-19 publications, assimilating and synthesizing information is challenging. Leveraging a robus...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2022-11-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2022/11/e34067 |