Machine learning in hip arthroscopy: A new frontier for enhanced visibility and surgical precision

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]

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Publication Details

Journal
German Medical Science (German Research Foundation)
Published
2025-10-31
DOI
https://doi.org/10.3205/25dkou648
Primary Topic
Hip disorders and treatments
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine learning in hip arthroscopy: A new frontier for enhanced visibility and surgical precision

German Medical Science (German Research Foundation)
Hip disorders and treatments
article

Machine learning in hip arthroscopy: A new frontier for enhanced visibility and surgical precision

article en

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]

German Medical Science (German Research Foundation)
TUM Klinikum (DE), Klinik und Poliklinik für Orthopädie, Physikalische Medizin und Rehabilitation (DE)
Quality Education
Openalex Percentile: Top 32%
Hip disorders and treatments
DOIOpen Access PDFOpenAlex
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Machine learning in hip arthroscopy: A new frontier for enhanced visibility and surgical precision · German Medical Science (German Research Foundation) (2025) | TGRS Research Map | TGRS