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

Natural Language Processing (650) Machine Learning (1401) Infodemiology and Infoveillance (1278) Pulmonology, COPD (126) Peer-to-Peer Support and Online Communities (602) Infoveillance and Social Listening (181) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1573) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26272, first published .
A Neural Network Approach for Understanding Patient Experiences of Chronic Obstructive Pulmonary Disease (COPD): Retrospective, Cross-sectional Study of Social Media Content

A Neural Network Approach for Understanding Patient Experiences of Chronic Obstructive Pulmonary Disease (COPD): Retrospective, Cross-sectional Study of Social Media Content

A Neural Network Approach for Understanding Patient Experiences of Chronic Obstructive Pulmonary Disease (COPD): Retrospective, Cross-sectional Study of Social Media Content

Authors of this article:

Tobe Che Benjamin Freeman1, 2 Author Orcid Image ;   Raul Rodriguez-Esteban1 Author Orcid Image ;   Juergen Gottowik1 Author Orcid Image ;   Xing Yang3 Author Orcid Image ;   Veit Johannes Erpenbeck4 Author Orcid Image ;   Mathias Leddin1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Byrom B, Bessant C, Smeraldi F, Abdollahyan M, Bridges Y, Chowdhury M, Tahsin A. Deriving Meaningful Aspects of Health Related to Physical Activity in Chronic Disease: Concept Elicitation Using Machine Learning–Assisted Coding of Online Patient Conversations. Value in Health 2023;26(7):1057 View
  2. Cimiano P, Collins B, De Vuono M, Escudier T, Gottowik J, Hartung M, Leddin M, Neupane B, Rodriguez-Esteban R, Schmidt A, Starke-Knäusel C, Voorhaar M, Wieckowski K. Patient listening on social media for patient-focused drug development: a synthesis of considerations from patients, industry and regulators. Frontiers in Medicine 2024;11 View