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

Chatbots and Conversational Agents (748) Text-messaging (SMS, WeChat etc)-Based Interventions (756) Artificial Intelligence (2162) Natural Language Processing (923) Mobile Health (mhealth) (3491)

Published on in Vol 24, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36151, first published .
Identifying Medication-Related Intents From a Bidirectional Text Messaging Platform for Hypertension Management Using an Unsupervised Learning Approach: Retrospective Observational Pilot Study

Identifying Medication-Related Intents From a Bidirectional Text Messaging Platform for Hypertension Management Using an Unsupervised Learning Approach: Retrospective Observational Pilot Study

Identifying Medication-Related Intents From a Bidirectional Text Messaging Platform for Hypertension Management Using an Unsupervised Learning Approach: Retrospective Observational Pilot Study

Authors of this article:

Anahita Davoudi1 Author Orcid Image ;   Natalie S Lee2 Author Orcid Image ;   ThaiBinh Luong3 Author Orcid Image ;   Timothy Delaney4 Author Orcid Image ;   Elizabeth Asch5 Author Orcid Image ;   Krisda Chaiyachati4, 5, 6 Author Orcid Image ;   Danielle Mowery1 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Alam S, Gonzalez Suarez M. Transforming Healthcare: The AI Revolution in the Comprehensive Care of Hypertension. Clinics and Practice 2024;14(4):1357 View
  2. Clay B, Bergman H, Salim S, Pergola G, Shalhoub J, Davies A. Natural language processing techniques applied to the electronic health record in clinical research and practice - an introduction to methodologies. Computers in Biology and Medicine 2025;188:109808 View