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 robust computational pipeline...
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| Main Authors: | , , , , , |
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| Format: | Book |
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JMIR Publications,
2022-11-01T00:00:00Z.
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Internet
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A1234.567 |
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| Copy 1 | Available |