Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients

We were able to develop predictive machine learning models that displayed predictive accuracy in predicting prolonged post-operative opioid use while improving model explainability and transparency.

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Publication Details

Journal
BMC Musculoskeletal Disorders
Published
2025-12-12
DOI
https://doi.org/10.1186/s12891-025-09301-8
Citations
2
Primary Topic
Opioid Use Disorder Treatment
Type
article
Field-Weighted Citation Impact
3.76
Controls
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article

Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients

Liane M. Miller, Bambang Parmanto, Albert Lin, Ahmad P. Tafti et al.
2 citations
BMC Musculoskeletal Disorders
Opioid Use Disorder Treatment
3.76
article

Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients

Liane M. Miller, Bambang Parmanto, Albert Lin, Ahmad P. Tafti, Jason Guattery, James J. Irrgang
article en
2 citations

Abstract

We were able to develop predictive machine learning models that displayed predictive accuracy in predicting prolonged post-operative opioid use while improving model explainability and transparency.

BMC Musculoskeletal DisordersVol. 26(1)
University of Pittsburgh (US), University of Pennsylvania (US)
Openalex Percentile: Top 6%
Opioid Use Disorder Treatment
3.76
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Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients — Liane M. Miller, Bambang Parmanto, et al. · BMC Musculoskeletal Disorders (2025) | TGRS Research Map | TGRS