Can machine learning predict the accuracy of preoperative planning for total hip arthroplasty, basing on patient-related factors? An explorative investigation on Supervised machine learning classification models

The success of Total Hip Arthroplasty (THA) is influenced by preoperative planning, with traditional 2D approaches displaying varied reliability as well. The present study investigates the use of Supervised Machine Learning (SML) models with patient-related features to improve accuracy. Preoperative...

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Veröffentlicht in:	Journal of clinical orthopaedics and trauma 2024-06, Vol.53, p.102470, Article 102470
Hauptverfasser:	Zampogna, B., Torre, G., Zampoli, A., Parisi, F., Ferrini, A., Shanmugasundaram, S., Franceschetti, E., Papalia, R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence K-Nearest Neighbors Preoperative planning Supervised machine learning Total hip arthroplasty
Online-Zugang:	Volltext
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