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

Discretionary Corrigenda (97)

Published on in Vol 25 (2023)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55010, first published .
Figure Correction: Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: Natural Language Processing Approach

Figure Correction: Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: Natural Language Processing Approach

Figure Correction: Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: Natural Language Processing Approach

Authors of this article:

Elham Dolatabadi1, 2, 3 Author Orcid Image ;   Diana Moyano2 Author Orcid Image ;   Michael Bales4 Author Orcid Image ;   Sofija Spasojevic4 Author Orcid Image ;   Rohan Bhambhoria5 Author Orcid Image ;   Junaid Bhatti6 Author Orcid Image ;   Shyamolima Debnath7 Author Orcid Image ;   Nicholas Hoell7 Author Orcid Image ;   Xin Li3 Author Orcid Image ;   Celine Leng4 Author Orcid Image ;   Sasha Nanda7 Author Orcid Image ;   Jad Saab8 Author Orcid Image ;   Esmat Sahak3 Author Orcid Image ;   Fanny Sie4 Author Orcid Image ;   Sara Uppal8 Author Orcid Image ;   Nirma Khatri Vadlamudi9 Author Orcid Image ;   Antoaneta Vladimirova10 Author Orcid Image ;   Artur Yakimovich11 Author Orcid Image ;   Xiaoxue Yang7 Author Orcid Image ;   Sedef Akinli Kocak2 Author Orcid Image ;   Angela M Cheung3, 12 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Conference Proceedings

  1. Hermawan A, Hafidz I, Rangkuti R, Latiffianti E, Rakhmawati N. 2024 International Conference on Decision Aid Sciences and Applications (DASA). Early Detection of Long COVID Symptoms from Social Media Using BERT View