Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach
Prediction of perioperative opioid needs using EMR and machine-learning is feasible and may support individualized pain management, though further refinement of model performance is warranted.
Authors
- June Y. Hou (ORCID: https://orcid.org/0000-0002-6022-0035)
- Judith S. Jacobson (ORCID: https://orcid.org/0000-0003-0916-6165)
- Pia M. Mauro (ORCID: https://orcid.org/0000-0003-2482-8841)
- Ana I. Tergas (ORCID: https://orcid.org/0000-0002-8752-2498)
- Yongmei Huang
- Jason D. Wright
- Xiao Xu
- Elena B. Elkin
- Silvia S. Martins
- Guohua Li
Institutions
- Rutgers, The State University of New Jersey (US)
- Johnson University (US)
- Columbia University (US)
Publication Details
- Journal
- Surgery Open Science
- Published
- 2026-01-20
- DOI
- https://doi.org/10.1016/j.sopen.2026.01.005
- Primary Topic
- Opioid Use Disorder Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00