Development and validation of an artificial intelligence model for the classification of hip fractures using the AO-OTA framework

Development and validation of an artificial intelligence model for the classification of hip fractures using the AO-OTA framework

Background and purpose: Artificial intelligence (AI) has the potential to aid in the accurate diagnosis of hip fractures and reduce the workload of clinicians. We primarily aimed to develop and validate a convolutional neural network (CNN) for the automated classification of hip fractures based on...

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Bibliographic Details
Main Authors: Ehsan Akbarian, Mehrgan Mohammadi, Emilia Tiala, Oscar Ljungberg, Ali Sharif Razavian, Martin Magnéli, Max Gordon
Format: Article
Language:English
Published: Medical Journals Sweden 2024-06-01
Series:Acta Orthopaedica
Subjects:
AO-OTA fracture classification
artificial intelligence
convolutional neural network
deep learning
hip fracture
Online Access:https://actaorthop.org/actao/article/view/40949

Internet

https://actaorthop.org/actao/article/view/40949

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