Is it feasible to develop a supervised learning algorithm incorporating spinopelvic mobility to predict impingement in patients undergoing total hip arthroplasty? a proof-of-concept study

Fontalis, A. orcid.org/0000-0001-5547-288X, Zhao, B., Putzeys, P. et al. (7 more authors) (2024) Is it feasible to develop a supervised learning algorithm incorporating spinopelvic mobility to predict impingement in patients undergoing total hip arthroplasty? a proof-of-concept study. Bone & Joint Open, 5 (8). pp. 671-680. ISSN 2633-1462

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Item Type: Article
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© 2024 Fontalis et al. This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial No Derivatives (CC BY-NC-ND 4.0) licence, which permits the copying and redistribution of the work only, and provided the original author and source are credited. See https:// creativecommons.org/licenses/by-nc-nd/4.0/

Keywords: Biomedical and Clinical Sciences; Clinical Sciences; Networking and Information Technology R&D (NITRD); Machine Learning and Artificial Intelligence; Bioengineering; Assistive Technology
Dates:
  • Published: 14 August 2024
  • Published (online): 14 August 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health
Depositing User: Symplectic Sheffield
Date Deposited: 15 Oct 2024 11:47
Last Modified: 15 Oct 2024 11:49
Status: Published
Publisher: British Editorial Society of Bone & Joint Surgery
Refereed: Yes
Identification Number: 10.1302/2633-1462.58.bjo-2024-0020.r1
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