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Division of Computing, Analytics and Mathematics

School of Science and Engineering, University of Missouri Kansas City

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Could Artificial Intelligence help in predicting opioid use disorders? All that glitters is not gold.

Cascella, Marco. 2025. “Could Artificial Intelligence Help in Predicting Opioid Use Disorders? All That Glitters Is Not Gold.”. Journal of Opioid Management 21 (5): 367-68.

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Last updated on 10/22/2025
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Recent Publications

Wavelet-Based Pattern ERG Biomarkers Outperform Temporal Amplitude Measures for Functional Stratification in Optic Nerve Disease.
A letter to the editor: Expanding the evidence base for ventilation feedback devices.
A randomised, exploratory study comparing a single episode of feedback with regular feedback and no feedback on ambulance clinician bag-valve-mask ventilation during a simulated cardiac arrest over a six-month time frame.
Ambulance service demand from prisons: a service evaluation.
Between the ambulance and academia: rethinking identity and competence in paramedics with reduced clinical exposure.
End-tidal carbon dioxide monitoring to predict hypovolaemic shock and the subsequent need for blood transfusions in adult pre-hospital trauma patients: a systematic review.

Liana Sega, Ph.D.

University of Missouri - Kansas City

Division of Computing, Analytics and Mathematics.

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