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

Artificial Intelligence in Surgery and Perioperative Medicine (24) Machine Learning (1401) Perioperative Software Tools for Clinicians (13)

Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39650, first published .
An Ensemble Learning Approach to Improving Prediction of Case Duration for Spine Surgery: Algorithm Development and Validation

An Ensemble Learning Approach to Improving Prediction of Case Duration for Spine Surgery: Algorithm Development and Validation

An Ensemble Learning Approach to Improving Prediction of Case Duration for Spine Surgery: Algorithm Development and Validation

Authors of this article:

Rodney Allanigue Gabriel1, 2 Author Orcid Image ;   Bhavya Harjai2 Author Orcid Image ;   Sierra Simpson2 Author Orcid Image ;   Austin Liu Du3 Author Orcid Image ;   Jeffrey Logan Tully2 Author Orcid Image ;   Olivier George4 Author Orcid Image ;   Ruth Waterman5 Author Orcid Image
Article Authors Cited by (7) Tweetations (4) Metrics

Journals

  1. Adams M, Nelson A, Narouze S. Daring discourse: artificial intelligence in pain medicine, opportunities and challenges. Regional Anesthesia & Pain Medicine 2023;48(9):439 View
  2. Arina P, Kaczorek M, Hofmaenner D, Pisciotta W, Refinetti P, Singer M, Mazomenos E, Whittle J. Prediction of Complications and Prognostication in Perioperative Medicine: A Systematic Review and PROBAST Assessment of Machine Learning Tools. Anesthesiology 2024;140(1):85 View
  3. Zeleke A, Palumbo P, Tubertini P, Miglio R, Chiari L. Machine learning-based prediction of hospital prolonged length of stay admission at emergency department: a Gradient Boosting algorithm analysis. Frontiers in Artificial Intelligence 2023;6 View
  4. Spence C, Shah O, Cebula A, Tucker K, Sochart D, Kader D, Asopa V. Machine learning models to predict surgical case duration compared to current industry standards: scoping review. BJS Open 2023;7(6) View
  5. Lippenberger F, Ziegelmayer S, Berlet M, Feussner H, Makowski M, Neumann P, Graf M, Kaissis G, Wilhelm D, Braren R, Reischl S. Development of an image-based Random Forest classifier for prediction of surgery duration of laparoscopic sigmoid resections. International Journal of Colorectal Disease 2024;39(1) View
  6. Bellini V, Russo M, Domenichetti T, Panizzi M, Allai S, Bignami E. Artificial Intelligence in Operating Room Management. Journal of Medical Systems 2024;48(1) View
  7. Zeleke A, Palumbo P, Tubertini P, Miglio R, Chiari L. Comparison of nine machine learning regression models in predicting hospital length of stay for patients admitted to a general medicine department. Informatics in Medicine Unlocked 2024;47:101499 View