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

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1954) Nephrology/Renal Disorders (109) Infodemiology and Infoveillance (1588) Infoveillance and Social Listening (320) Natural Language Processing (943)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70128, first published .
Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse

Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse

Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse

Authors of this article:

Ravi Shankar1 Author Orcid Image ;   Qian Xu2 Author Orcid Image ;   Anjali Bundele1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

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  2. Di Maria A, Capone M, Mancini R, De Giorgi A, Gavazzoli E, Scichilone L, Veronesi M, Nicoletti S, Fabbian F. Detection of Financial Toxicity in Italian Uremic Patients: A Single Center Cross-Sectional Study. International Journal of Nephrology and Renovascular Disease 2025;Volume 18:361 View
  3. Joshi S, Mehta M, Maniar S, Wang M, Singh V. Performance of Large Language Models Under Input Variability in Health Care Applications: Dataset Development and Experimental Evaluation. JMIR AI 2026;5:e83640 View