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

JMIR Theme Issue: COVID-19 Special Issue (2554) Innovative Methods in Public Health and Surveillance (383) Registered Report (791) Clinical Information and Decision Making (1915) Infodemiology and Infoveillance (1558) Natural Language Processing (917) Artificial Intelligence (2129) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45767, first published .
Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: Natural Language Processing Approach

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

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 (9) Tweetations (13) Metrics

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  3. Mfouth Kemajou P, Mbanya A, Coppieters Y. Digital approaches in post-COVID healthcare: a systematic review of technological innovations in disease management. Biology Methods and Protocols 2024;9(1) View
  4. Scherbakov D, Hubig N, Lenert L, Alekseyenko A, Obeid J. Natural Language Processing and Social Determinants of Health in Mental Health Research: AI-Assisted Scoping Review. JMIR Mental Health 2025;12:e67192 View
  5. Raza S, Shaban-Nejad A, Dolatabadi E, Mamiya H. Exploring Bias and Prediction Metrics to Characterise the Fairness of Machine Learning for Equity-Centered Public Health Decision-Making: A Narrative Review. IEEE Access 2024;12:180815 View
  6. Ohno Y, Aomori T, Nishiyama T, Kato R, Fujiki R, Ishikawa H, Kiyomiya K, Isawa M, Mochizuki M, Aramaki E, Ohtani H. Performance Improvement of a Natural Language Processing Tool for Extracting Patient Narratives Related to Medical States From Japanese Pharmaceutical Care Records by Increasing the Amount of Training Data: Natural Language Processing Analysis and Validation Study. JMIR Medical Informatics 2025;13:e68863 View
  7. Obadinma S, Lachana A, Norman M, Rankin J, Yu J, Zhu X, Mastropaolo D, Pandya D, Sultan R, Dolatabadi E. The FAIIR conversational AI agent assistant for youth mental health service provision. npj Digital Medicine 2025;8(1) View
  8. Hossain B, Preum S, Rabbi M, Ara R, Ali M. Extracting Symptoms of Complex Conditions From Online Discourse (Subreddit to Symptomatology): Lexicon-Based Approach. JMIR Medical Informatics 2025;13:e70940 View

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  1. Thakur N, Fernandes N, Tchona M. HCI International 2025 Posters. View