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

JMIR Theme Issue: COVID-19 Special Issue (2094) Machine Learning (1009) Outbreak and Pandemic Preparedness and Management (1458) Artificial Intelligence (669) Natural Language Processing (492)

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 Pal 1 Author Orcid Image ;   Harshita Chopra 2 Author Orcid Image ;   Raghav Awasthi 1 Author Orcid Image ;   Harsh Bandhey 1 Author Orcid Image ;   Aditya Nagori 1, 3 Author Orcid Image ;   Tavpritesh Sethi 1 Author Orcid Image
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