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

JMIR Theme Issue: COVID-19 Special Issue (2391) Data Science (225) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1482) Artificial Intelligence (1198) Machine Learning (1385)

Published on in Vol 24, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38584, first published .
Deep Denoising of Raw Biomedical Knowledge Graph From COVID-19 Literature, LitCovid, and Pubtator: Framework Development and Validation

Deep Denoising of Raw Biomedical Knowledge Graph From COVID-19 Literature, LitCovid, and Pubtator: Framework Development and Validation

Deep Denoising of Raw Biomedical Knowledge Graph From COVID-19 Literature, LitCovid, and Pubtator: Framework Development and Validation

Authors of this article:

Chao Jiang1 Author Orcid Image ;   Victoria Ngo2, 3, 4 Author Orcid Image ;   Richard Chapman1 Author Orcid Image ;   Yue Yu5 Author Orcid Image ;   Hongfang Liu5 Author Orcid Image ;   Guoqian Jiang5 Author Orcid Image ;   Nansu Zong5 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

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  1. Modesitt E, Yang R, Liu Q. HCI International 2023 Posters. View
  2. Murungi N, Pham M, Dai X, Qu X. HCI International 2023 – Late Breaking Papers. View
  3. Yunoki I, Berreby G, D’Andrea N, Lu Y, Qu X. HCI International 2023 – Late Breaking Posters. View