Diagnostic performance of deep learning for leg length measurements on radiographs in leg length discrepancy: A systematic review

Diagnostic performance of deep learning for leg length measurements on radiographs in leg length discrepancy: A systematic review

Abstract Purpose To systematically review the literature regarding machine learning in leg length discrepancy (LLD) and to provide insight into the most relevant manuscripts on this topic in order to highlight the importance and future clinical implications of machine learning in the diagnosis and t...

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Bibliographic Details
Main Authors: Bradley A. Lezak, James A. Pruneski, Jacob F. Oeding, Kyle N. Kunze, Riley J. Williams III, Michael J. Alaia, Andrew D. Pearle, Joshua S. Dines, Kristian Samuelsson, Ayoosh Pareek
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Journal of Experimental Orthopaedics
Subjects:
artificial intelligence
deep learning
diagnostic imaging
machine learning
orthopaedics
Online Access:https://doi.org/10.1002/jeo2.70080
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