This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2452) Machine Learning (1465) Outbreak and Pandemic Preparedness and Management (1727) Artificial Intelligence (1371) Natural Language Processing (693)

Published on in Vol 24, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34067, first published .
Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature With Unsupervised Word Embeddings and Machine Learning: Evidence-Based Study

Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature With Unsupervised Word Embeddings and Machine Learning: Evidence-Based Study

Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature With Unsupervised Word Embeddings and Machine Learning: Evidence-Based Study

Authors of this article:

Ridam Pal1 Author Orcid Image ;   Harshita Chopra2 Author Orcid Image ;   Raghav Awasthi1 Author Orcid Image ;   Harsh Bandhey1 Author Orcid Image ;   Aditya Nagori1, 3 Author Orcid Image ;   Tavpritesh Sethi1 Author Orcid Image
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