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

Aims: Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of o...

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Veröffentlicht in:	Bone & joint open Jg. 5; H. 8; S. 671 - 680
Hauptverfasser:	Fontalis, Andreas, Zhao, Baixiang, Putzeys, Pierre, Mancino, Fabio, Zhang, Shuai, Vanspauwen, Thomas, Glod, Fabrice, Plastow, Ricci, Mazomenos, Evangelos, Haddad, Fares S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London The British Editorial Society of Bone & Joint Surgery 14.08.2024
Schlagworte:	acetabular component Arthroplasty artificial intelligence biomechanics flexion Hip hips impingement offset pelvic incidence pelvis prospective cohort study radiographs Reverse Hybrid robotic arm robotic-arm assistance sacral slope spinopelvic mobility supervised learning total hip arthroplasty total hip arthroplasty (tha) virtual range of motion
ISSN:	2633-1462, 2633-1462
Online-Zugang:	Volltext
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