Machine learning in hip arthroscopy: A new frontier for enhanced visibility and surgical precision
Year: 2025
Type: conference-paper
Abstract: Objectives and questions: Success of technically challenging hip arthroscopy for femoroacetabular impingement syndrome (FAIS) with demanding (steep) learning curve and increased risk of complications critically depends on optimal intraoperative visualization. For the first, time Machine Learning Algorithm [for full text, please go to the a.m. URL]
DOI: 10.3205/25dkou648
Authors: Twardy, Vanessa, Hinterwimmer, Florian, Fütterer, Cornelia, Haller, Bernhard, Hömann, Niklas, Willinger, Lukas, Blobner, Kilian, von Eisenhart-Rothe, Rüdiger, Banke, Ingo
Institutions: TUM Klinikum, Technical University of Munich
Language: English
Topic: Hip disorders and treatments
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7103149591
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