Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44909, first published .
Machine Learning for the Prediction of Procedural Case Durations Developed Using a Large Multicenter Database: Algorithm Development and Validation Study

Machine Learning for the Prediction of Procedural Case Durations Developed Using a Large Multicenter Database: Algorithm Development and Validation Study

Machine Learning for the Prediction of Procedural Case Durations Developed Using a Large Multicenter Database: Algorithm Development and Validation Study

Journals

  1. Rohatgi N. JMIR Perioperative Medicine: A Global Journal for Publishing Interdisciplinary Innovations, Research, and Perspectives. JMIR Perioperative Medicine 2023;6:e54344 View
  2. Loukas C, Seimenis I, Prevezanou K, Schizas D. Prediction of remaining surgery duration in laparoscopic videos based on visual saliency and the transformer network. The International Journal of Medical Robotics and Computer Assisted Surgery 2024;20(2) View
  3. El Emam K, Leung T, Malin B, Klement W, Eysenbach G. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS). Journal of Medical Internet Research 2024;26:e52508 View
  4. Meyers A, Daysalilar M, Dagal A, Wang M, Kutlu O, Akcin M. Quantifying the impact of surgical teams on each stage of the operating room process. Frontiers in Digital Health 2024;6 View