Deep learning for early detection of pathological changes in X-ray bone microstructures: case of osteoarthritis
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Title
Deep learning for early detection of pathological changes in X-ray bone microstructures: case of osteoarthritis
Authors
Keywords
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Journal
Scientific Reports
Volume 11, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2021-01-27
DOI
10.1038/s41598-021-81786-4
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Note: Only part of the references are listed.- The impact of osteoarthritis on early exit from work: results from a population-based study
- (2018) Pedro A. Laires et al. BMC PUBLIC HEALTH
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- (2017) Richard Ljuhar et al. RHEUMATOLOGY
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- (2017) Sergey V. Minaev et al. WORLD JOURNAL OF SURGERY
- SAT0557 A Clinical Study To Examine Thresholds of Joint Space Width and Joint Space Area for Identification of Knee Osteoarthritis
- (2016) R. Ljuhar et al. ANNALS OF THE RHEUMATIC DISEASES
- FRI0545 A Novel Feature Selection Algorithm Based on Bone Micro Architecture Analysis To Identify Osteoarthritis
- (2016) R. Ljuhar et al. ANNALS OF THE RHEUMATIC DISEASES
- Classifications in Brief: Kellgren-Lawrence Classification of Osteoarthritis
- (2016) Mark D. Kohn et al. CLINICAL ORTHOPAEDICS AND RELATED RESEARCH
- Baseline trabecular bone and its relation to incident radiographic knee osteoarthritis and increase in joint space narrowing score: directional fractal signature analysis in the MOST study
- (2016) P. Podsiadlo et al. OSTEOARTHRITIS AND CARTILAGE
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Quantification of differences in bone texture from plain radiographs in knees with and without osteoarthritis
- (2014) J. Hirvasniemi et al. OSTEOARTHRITIS AND CARTILAGE
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Trabecular bone texture detected by plain radiography is associated with an increased risk of knee replacement in patients with osteoarthritis: a 6 year prospective follow up study
- (2013) P. Podsiadlo et al. OSTEOARTHRITIS AND CARTILAGE
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- (2011) T. Woloszynski et al. ARTHRITIS AND RHEUMATISM
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- (2009) L. Shamir et al. OSTEOARTHRITIS AND CARTILAGE
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- (2008) L. Shamir et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
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