Development and Validation of a Multitask Deep Learning Model for Severity Grading of Hip Osteoarthritis Features on Radiographs-Reference-Cited by-同舟云学术

Development and Validation of a Multitask Deep Learning Model for Severity Grading of Hip Osteoarthritis Features on Radiographs

Published:2020-04 Issue:1 Volume:295 Page:136-145
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

von Schacky Claudio E.^ORCID,Sohn Jae Ho^ORCID,Liu Felix^ORCID,Ozhinsky Eugene^ORCID,Jungmann Pia M.^ORCID,Nardo Lorenzo^ORCID,Posadzy Magdalena^ORCID,Foreman Sarah C.^ORCID,Nevitt Michael C.^ORCID,Link Thomas M.^ORCID,Pedoia Valentina

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2020190925

Reference20 articles.

1. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

2. Incidence and risk factors for clinically diagnosed knee, hip and hand osteoarthritis: influences of age, gender and osteoarthritis affecting other joints

3. Prevalence of Radiographic and Symptomatic Hip Osteoarthritis in an Urban United States Community: The Framingham Osteoarthritis Study

4. The American College of Rheumatology criteria for the classification and reporting of osteoarthritis of the hip

5. Atlas of individual radiographic features in osteoarthritis, revised

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