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

Artificial Intelligence (1204) Opioid and Related Substance Misuse (127) Machine Learning (1388) Text-messaging (SMS, WeChat etc)-Based Interventions (622)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44165, first published .
An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

Authors of this article:

John D Piette1, 2 Author Orcid Image ;   Laura Thomas1, 3 Author Orcid Image ;   Sean Newman1, 2 Author Orcid Image ;   Nicolle Marinec1, 2 Author Orcid Image ;   Joel Krauss4 Author Orcid Image ;   Jenny Chen1, 2 Author Orcid Image ;   Zhenke Wu5 Author Orcid Image ;   Amy S B Bohnert1, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations (13) Metrics

Journals

  1. Bucher A, Blazek E, Symons C. How Are Machine Learning and Artificial Intelligence Used in Digital Behavior Change Interventions? A Scoping Review. Mayo Clinic Proceedings: Digital Health 2024 View
  2. Mazzolenis M, Bulat E, Schatman M, Gumb C, Gilligan C, Yong R. The Ethical Stewardship of Artificial Intelligence in Chronic Pain and Headache: A Narrative Review. Current Pain and Headache Reports 2024 View