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

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Natural Language Processing (770) Machine Learning (1654)

Published on in Vol 10, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37884, first published .
Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study

Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study

Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study

Authors of this article:

Mohsen Asghari1 Author Orcid Image ;   Joshua Nielsen2 Author Orcid Image ;   Monica Gentili2 Author Orcid Image ;   Naoru Koizumi3 Author Orcid Image ;   Adel Elmaghraby1 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Crenshaw R, Woods C, Koizumi N, Dave H, Gentili M, Saleem J. Understanding Barriers and Facilitators to Living Kidney Donation Within a Sociotechnical Systems Framework. Qualitative Health Research 2024;34(7):691 View
  2. Nielsen J, Chen X, Davis L, Waterman A, Gentili M. Investigating the Classification of Living Kidney Donation Experiences on Reddit and Understanding the Sensitivity of ChatGPT to Prompt Engineering: Content Analysis. JMIR AI 2025;4:e57319 View
  3. Gatsinga R, Lau R, Lim B, Fong K, Yeong M, Chung A, Ng L, Aslim E, Gan V, Lim E. Current Applications and Developments of Natural Language Processing in Kidney Transplantation: A Scoping Review. Transplantation Proceedings 2025 View