Unveiling surgical expertise through machine learning in a novel VR/AR spinal simulator: A multilayered approach using transfer learning and connection weights analysis-Reference-Cited by-同舟云学术

Unveiling surgical expertise through machine learning in a novel VR/AR spinal simulator: A multilayered approach using transfer learning and connection weights analysis

Published:2024-09 Issue: Volume:179 Page:108809
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Alkadri Sami^ORCID,Del Maestro Rolando F.,Driscoll Mark^ORCID

Funder

Royal College of Physicians and Surgeons of Canada

Montreal Neurological Institute and Hospital

NSERC

Publisher

Elsevier BV

Reference35 articles.

1. Surgical education, simulation, and simulators-updating the concept of validity;Goldenberg;Curr. Urol. Rep.,2018

2. Virtual reality training in laparoscopic surgery: a systematic review & meta-analysis;Alaker;Int. J. Surg.,2016

3. S. Alkadri, R. F. Del Maestro, and M. Driscoll, "Face, content, and construct validity of a novel VR/AR surgical simulator of a minimally invasive spine operation," Med. Biol. Eng. Comput.

4. Analysis of surgical forces required to gain access using a probe for minimally invasive spine surgery via cadaveric-based experiments towards use in training simulators;El-Monajjed;IEEE (Inst. Electr. Electron. Eng.) Trans. Biomed. Eng.,2020

5. Kinematic study and layout design of a haptic device mounted on a spine bench model for surgical training;Alkadri,2018

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