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

JMIR Theme Issue: COVID-19 Special Issue (2452) Natural Language Processing (693) Machine Learning (1465) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infectious Diseases (non-STD/STI) (1575) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Infodemiology and Infoveillance (1349)

Published on in Vol 24, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30397, first published .
Monitoring COVID-19 on Social Media: Development of an End-to-End Natural Language Processing Pipeline Using a Novel Triage and Diagnosis Approach

Monitoring COVID-19 on Social Media: Development of an End-to-End Natural Language Processing Pipeline Using a Novel Triage and Diagnosis Approach

Monitoring COVID-19 on Social Media: Development of an End-to-End Natural Language Processing Pipeline Using a Novel Triage and Diagnosis Approach

Authors of this article:

Abul Hasan1 Author Orcid Image ;   Mark Levene1 Author Orcid Image ;   David Weston1 Author Orcid Image ;   Renate Fromson2 Author Orcid Image ;   Nicolas Koslover2 Author Orcid Image ;   Tamara Levene2 Author Orcid Image
Article Authors Cited by (6) Tweetations (13) Metrics

Abul Hasan   1 , MSc ;   Mark Levene   1 , PhD ;   David Weston   1 , PhD ;   Renate Fromson   2 , MBBS ;   Nicolas Koslover   2 , BMBCh ;   Tamara Levene   2 , BMBCh

1 Department of Computer Science and Information Systems, Birkbeck, University of London, London, United Kingdom

2 Barnet General Hospital, London, United Kingdom

Corresponding Author:

  • Abul Hasan, MSc
  • Department of Computer Science and Information Systems
  • Birkbeck, University of London
  • Malet Street, Bloomsbury
  • London, WC1E 7HX
  • United Kingdom
  • Phone: 44 020 7631 8147
  • Email: abulhasan@dcs.bbk.ac.uk