Published on in Vol 13 (2025)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70857, first published .
Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization: Retrospective Study

Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization: Retrospective Study

Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization: Retrospective Study

Journals

  1. Yao X, Rao A, Padman R. Analytical approaches for medication management for patient safety: a scoping review. npj Health Systems 2025;2(1) View
  2. Abbas A, Saleh I, Wong P, Larouche J, Abouali J, Park S, Chan T, Sarhangian V, Toor J. Optimizing Daily Surgical Scheduling Improves Operative Time Consumption: A Retrospective Study. Arthroplasty Today 2026:101926 View
  3. Baigarayeva Z, Boltaboyeva A, Imanbek B, Amangeldy B, Tasmurzayev N, Ozhikenov K, Ozhiken A, Alimbayeva Z, Maeda-Nishino N. Non-Imaging Differential Diagnosis of Lower Limb Osteoarthritis: An Interpretable Machine Learning Framework. Algorithms 2026;19(1):87 View
  4. Lex J, Abbas A, Toor J, Khalil E, Ravi B, Whyne C. Smart scheduling of arthroplasty surgery with machine learning and optimisation improves operating room utilisation. BMJ Health & Care Informatics 2026;33(1):e101420 View
  5. Magouliotis D, Sicouri N, Ramlawi L, Baudo M, Androutsopoulou V, Sicouri S. Artificial Intelligence in Adult Cardiovascular Medicine and Surgery: Real-World Deployments and Outcomes. Journal of Personalized Medicine 2026;16(2):69 View
  6. Dexter F, Fahy B, Epstein R. Percentages of Surgical Procedure Combinations That Were Performed Just Once or Twice at Florida Hospital and Ambulatory Surgery Centers During Each Quarter From 2010 Through 2024. Cureus 2026 View