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

JMIR Theme Issue: COVID-19 Special Issue (2452) Data Science (270) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Artificial Intelligence (1371) Machine Learning (1465)

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 (5) Tweetations (3) Metrics

Chao Jiang   1 , BS ;   Victoria Ngo   2, 3, 4 , PhD ;   Richard Chapman   1 , PhD ;   Yue Yu   5 , PhD ;   Hongfang Liu   5 , PhD ;   Guoqian Jiang   5 , MD, PhD ;   Nansu Zong   5 , PhD

1 Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, United States

2 Center for Innovation to Implementation, VA Palo Alto Health Care System, Sacramento, CA, United States

3 Stanford Health Policy, Stanford School of Medicine, Stanford University, Stanford, CA, United States

4 Freeman Spogli Institute for International Studies, Stanford University, Stanford, CA, United States

5 Department of Artificial Intelligence and Informatics Research, Mayo Clinic, Rochester, MN, United States

Corresponding Author:

  • Nansu Zong, PhD
  • Department of Artificial Intelligence and Informatics Research
  • Mayo Clinic
  • 200 First St SW
  • Rochester, MN, 55905
  • United States
  • Phone: 1 507-284-2511
  • Email: Zong.Nansu@mayo.edu