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

Public Health Informatics (135) JMIR Theme Issue: COVID-19 Special Issue (2555) Infectious Diseases (non-STD/STI) (1727) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1543) Outbreak and Pandemic Preparedness and Management (1827) Surveillance Systems (514) Digital Contact Tracing, Digital Proximity Tracing, Precision Public Health (161) Innovative Methods in Public Health and Surveillance (385) Natural Language Processing (919)

Published on in Vol 8, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36119, first published .
Identifying COVID-19 Outbreaks From Contact-Tracing Interview Forms for Public Health Departments: Development of a Natural Language Processing Pipeline

Identifying COVID-19 Outbreaks From Contact-Tracing Interview Forms for Public Health Departments: Development of a Natural Language Processing Pipeline

Identifying COVID-19 Outbreaks From Contact-Tracing Interview Forms for Public Health Departments: Development of a Natural Language Processing Pipeline

Authors of this article:

John Caskey1 Author Orcid Image ;   Iain L McConnell1 Author Orcid Image ;   Madeline Oguss1 Author Orcid Image ;   Dmitriy Dligach2 Author Orcid Image ;   Rachel Kulikoff3 Author Orcid Image ;   Brittany Grogan3 Author Orcid Image ;   Crystal Gibson3 Author Orcid Image ;   Elizabeth Wimmer4 Author Orcid Image ;   Traci E DeSalvo4 Author Orcid Image ;   Edwin E Nyakoe-Nyasani4 Author Orcid Image ;   Matthew M Churpek1 Author Orcid Image ;   Majid Afshar1 Author Orcid Image
Article Authors Cited by (4) Tweetations (13) Metrics

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  2. Olawade D, Wada O, David-Olawade A, Kunonga E, Abaire O, Ling J. Using artificial intelligence to improve public health: a narrative review. Frontiers in Public Health 2023;11 View
  3. Lee S, Kim L, Shim M, Kim G. Identifying Health Care Services Offered in the HIV Care Continuum via a Machine Learning–Based Topic Modeling Approach: Exploratory Literature Review. JMIR Public Health and Surveillance 2025;11:e65081 View
  4. Cheon S, Ahn I. Survice-BERT: A BERT Model for Named Entity Recognition in Infectious Disease Surveillance Reports. Journal of Bacteriology and Virology 2025;55(3):235 View