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Machine learning in shoulder arthroplasty: a systematic review of predictive analytics applications

Aims: Machine learning (ML) holds significant promise in optimizing various aspects of total shoulder arthroplasty (TSA), potentially improving patient outcomes and enhancing surgical decision-making. The aim of this systematic review was to identify ML algorithms and evaluate their effectiveness,...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Tim Schneller, Moritz Kraus, Jan Schätz, Philipp Moroder, Markus Scheibel, Asimina Lazaridou
Format: Artigo
Sprache:Inglês
Veröffentlicht: The British Editorial Society of Bone & Joint Surgery 2025-02-01
Schriftenreihe:Bone & Joint Open
Schlagworte:
machine learning
systematic review
total shoulder arthroplasty
clinical outcomes
image analysis
predictive analytics
shoulder arthroplasty
rtsa
shoulder surgeries
imaging studies
clinicians
shoulder prosthesis
orthopaedic surgery
augmentation
Online-Zugang:https://online.boneandjoint.org.uk/doi/epdf/10.1302/2633-1462.62.BJO-2024-0234.R1
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