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

Theme Issue: Medical Informatics and COVID-19 (123) Data Science (349) JMIR Theme Issue: COVID-19 Special Issue (2543) Big Data (306) Natural Language Processing (879) Ontologies, Classifications, and Coding (315) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1540)

Published on in Vol 9, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21679, first published .
Lexicon Development for COVID-19-related Concepts Using Open-source Word Embedding Sources: An Intrinsic and Extrinsic Evaluation

Lexicon Development for COVID-19-related Concepts Using Open-source Word Embedding Sources: An Intrinsic and Extrinsic Evaluation

Lexicon Development for COVID-19-related Concepts Using Open-source Word Embedding Sources: An Intrinsic and Extrinsic Evaluation

Authors of this article:

Soham Parikh1 Author Orcid Image ;   Anahita Davoudi2 Author Orcid Image ;   Shun Yu3 Author Orcid Image ;   Carolina Giraldo4 Author Orcid Image ;   Emily Schriver5 Author Orcid Image ;   Danielle Mowery6 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Mandal S, Wiesenfeld B, Mann D, Lawrence K, Chunara R, Testa P, Nov O. Evidence for Telemedicine’s Ongoing Transformation of Health Care Delivery Since the Onset of COVID-19: Retrospective Observational Study. JMIR Formative Research 2022;6(10):e38661 View
  2. Fieldhouse J, Ge J, Randhawa N, Wolking D, Genovese B, Mazet J, Desai A. The intersection of artificial intelligence with qualitative or mixed methods for communicable disease research: a scoping review. Public Health 2025;248:105961 View

Books/Policy Documents

  1. Rani S, Jain A. Intelligent Computing Systems and Applications. View