Published on in Vol 2, No 1 (2022): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35446, first published .
Unsupervised Machine Learning to Detect and Characterize Barriers to Pre-exposure Prophylaxis Therapy: Multiplatform Social Media Study

Unsupervised Machine Learning to Detect and Characterize Barriers to Pre-exposure Prophylaxis Therapy: Multiplatform Social Media Study

Unsupervised Machine Learning to Detect and Characterize Barriers to Pre-exposure Prophylaxis Therapy: Multiplatform Social Media Study

Journals

  1. Xu Q, McMann T, Godinez H, Nali M, Li J, Cai M, Merenda C, Lee C, Araojo R, Mackey T. Impact of COVID-19 on HIV Prevention Access: A Multi-platform Social Media Infodemiology Study. AIDS and Behavior 2023;27(6):1886 View
  2. Honcharov V, Li J, Sierra M, Rivadeneira N, Olazo K, Nguyen T, Mackey T, Sarkar U. Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis. JMIR Infodemiology 2023;3:e40575 View
  3. Mutai C, McSharry P, Ngaruye I, Musabanganji E. Use of unsupervised machine learning to characterise HIV predictors in sub-Saharan Africa. BMC Infectious Diseases 2023;23(1) View
  4. Godinez H, Xu Q, McMann T, Li J, Mackey T. Analysis of online user discussions on Reddit associated with the transition of use between HIV PrEP therapy. Frontiers in Public Health 2023;11 View
  5. Young L, Nan Y, Jang E, Stevens R. Digital Epidemiological Approaches in HIV Research: a Scoping Methodological Review. Current HIV/AIDS Reports 2023;20(6):470 View
  6. McMann T, Wenzel C, Le N, Li Z, Xu Q, Cuomo R, Mackey T. Detection and Characterization of Web-Based Pediatric COVID-19 Vaccine Discussions and Racial and Ethnic Minority Topics: Retrospective Analysis of Twitter Data. JMIR Pediatrics and Parenting 2023;6:e48004 View