Detection and localisation of hip fractures on anteroposterior radiographs with artificial intelligence: proof of concept

Volume: 75, Issue: 3, Pages: 237.e1 - 237.e9
Published: Mar 1, 2020
Abstract
To investigate the feasibility of applying a deep convolutional neural network (CNN) for detection/localisation of acute proximal femoral fractures (APFFs) on hip radiographs.This study had institutional review board approval. Radiographs of 307 patients with APFFs and 310 normal patients were identified. A split ratio of 3/1/1 was used to create training, validation, and test datasets. To test the validity of the proposed model, a 20-fold...
Paper Details
Title
Detection and localisation of hip fractures on anteroposterior radiographs with artificial intelligence: proof of concept
Published Date
Mar 1, 2020
Volume
75
Issue
3
Pages
237.e1 - 237.e9
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.