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

Development and Evaluation of Research Methods, Instruments and Tools (765) Mobile Health (mhealth) (3515) Formative Evaluation of Digital Health Interventions (3304) Substance Abuse (540) Opioid and Related Substance Misuse (205) Artificial Intelligence (2198)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45434, first published .
An Artificial Intelligence–Based Smartphone App for Assessing the Risk of Opioid Misuse in Working Populations Using Synthetic Data: Pilot Development Study

An Artificial Intelligence–Based Smartphone App for Assessing the Risk of Opioid Misuse in Working Populations Using Synthetic Data: Pilot Development Study

An Artificial Intelligence–Based Smartphone App for Assessing the Risk of Opioid Misuse in Working Populations Using Synthetic Data: Pilot Development Study

Authors of this article:

A B M Rezbaul Islam1 Author Orcid Image ;   Khalid M Khan2 Author Orcid Image ;   Amanda Scarbrough2 Author Orcid Image ;   Mariah Jade Zimpfer2 Author Orcid Image ;   Navya Makkena1 Author Orcid Image ;   Adebola Omogunwa2 Author Orcid Image ;   Sheikh Iqbal Ahamed3 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

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  2. Gabriel R, Park B, Hsu C, Macias A. A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations. Current Pain and Headache Reports 2025;29(1) View
  3. El-Helaly M. Artificial Intelligence and Occupational Health and Safety, Benefits and Drawbacks. La Medicina del Lavoro 2024;115(2):e2024014 View

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  1. Singgih M, Noufridhan Arzhanie A, Yasnita F, Budianto F. 2025 Innovations in Power and Advanced Computing Technologies (i-PACT). The Impact of AI on Worker Productivity: A Systematic Literature Review View