Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance

Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance

Abstract Background Radiographs of the sacroiliac joints are commonly used for the diagnosis and classification of axial spondyloarthritis. The aim of this study was to develop and validate an artificial neural network for the detection of definite radiographic sacroiliitis as a manifestation of axi...

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Bibliographic Details
Main Authors: Keno K. Bressem, Janis L. Vahldiek, Lisa Adams, Stefan Markus Niehues, Hildrun Haibel, Valeria Rios Rodriguez, Murat Torgutalp, Mikhail Protopopov, Fabian Proft, Judith Rademacher, Joachim Sieper, Martin Rudwaleit, Bernd Hamm, Marcus R. Makowski, Kay-Geert Hermann, Denis Poddubnyy
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Arthritis Research & Therapy
Subjects:
Axial spondyloarthritis
Sacroiliitis
Artificial intelligence
Deep learning
Machine learning
Online Access:https://doi.org/10.1186/s13075-021-02484-0

Internet

https://doi.org/10.1186/s13075-021-02484-0

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