AI MSK clinical applications: cartilage and osteoarthritis

A review of medical image data augmentation techniques for deep learning applications

(2021) Phillip Chlap et al.   Journal of Medical Imaging and Radiation Oncology

Machine learning to predict incident radiographic knee osteoarthritis over 8 Years using combined MR imaging features, demographics, and clinical factors: data from the Osteoarthritis Initiative

(2021) G.B. Joseph et al.   OSTEOARTHRITIS AND CARTILAGE

Deep learning risk assessment models for predicting progression of radiographic medial joint space loss over a 48-MONTH follow-up period

(2020) B. Guan et al.   OSTEOARTHRITIS AND CARTILAGE

Deep learning approach to predict pain progression in knee osteoarthritis

(2020) B. Guan et al.   OSTEOARTHRITIS AND CARTILAGE

Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images

(2020) Aniket A. Tolpadi et al.   Scientific Reports

Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data

(2020) Paweł Widera et al.   Scientific Reports

T 2 analysis of the entire osteoarthritis initiative dataset

(2020) Alaleh Razmjoo et al.   JOURNAL OF ORTHOPAEDIC RESEARCH

Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative

(2020) Kevin Leung et al.   RADIOLOGY

A machine learning-based diagnostic model associated with knee osteoarthritis severity

(2020) Soon Bin Kwon et al.   Scientific Reports

Explainable AI: A Review of Machine Learning Interpretability Methods

(2020) Pantelis Linardatos et al.   Entropy

Automatic knee meniscus tear detection and orientation classification with Mask-RCNN

(2019) V. Couteaux et al.   Diagnostic and Interventional Imaging

Artificial intelligence to diagnose meniscus tears on MRI

(2019) V. Roblot et al.   Diagnostic and Interventional Imaging

Diagnosing Osteoarthritis from T2 Maps using Deep Learning: An Analysis of the Entire Osteoarthritis Initiative Baseline Cohort

(2019) Valentina Pedoia et al.   OSTEOARTHRITIS AND CARTILAGE

Deep Learning for Detection of Complete Anterior Cruciate Ligament Tear

(2019) Peter D. Chang et al.   JOURNAL OF DIGITAL IMAGING

A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: Data from the OsteoArthritis Initiative

(2019) Abdelbasset Brahim et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium

(2019) A.E. Nelson et al.   OSTEOARTHRITIS AND CARTILAGE

Predicting knee osteoarthritis severity: comparative modeling based on patient’s data and plain X-ray images

(2019) Jaynal Abedin et al.   Scientific Reports

Automated cartilage and meniscus segmentation of knee MRI with conditional generative adversarial networks

(2019) Sibaji Gaj et al.   MAGNETIC RESONANCE IN MEDICINE

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data

(2019) Aleksei Tiulpin et al.   Scientific Reports

Effect of intra-articular injection of intermediate-weight hyaluronic acid on hip and knee cartilage: in-vivo evaluation using T2 mapping

(2018) Giulio Ferrero et al.   EUROPEAN RADIOLOGY

A Novel Method to Predict Knee Osteoarthritis Progression on MRI Using Machine Learning Methods

(2018) Yaodong Du et al.   IEEE TRANSACTIONS ON NANOBIOSCIENCE

Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach

(2018) Aleksei Tiulpin et al.   Scientific Reports

Clinical Implications and Challenges of Artificial Intelligence and Deep Learning

(2018) William W. Stead   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Modeling and predicting osteoarthritis progression: data from the osteoarthritis initiative

(2018) E. Halilaj et al.   OSTEOARTHRITIS AND CARTILAGE

Deep Learning Approach for Evaluating Knee MR Images: Achieving High Diagnostic Performance for Cartilage Lesion Detection

(2018) Fang Liu et al.   RADIOLOGY

Applying Densely Connected Convolutional Neural Networks for Staging Osteoarthritis Severity from Plain Radiographs

(2018) Berk Norman et al.   JOURNAL OF DIGITAL IMAGING

3D convolutional neural networks for detection and severity staging of meniscus and PFJ cartilage morphological degenerative changes in osteoarthritis and anterior cruciate ligament subjects

(2018) Valentina Pedoia et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Machine-learning-based patient-specific prediction models for knee osteoarthritis

(2018) Afshin Jamshidi et al.   Nature Reviews Rheumatology

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

(2018) Nicholas Bien et al.   PLOS MEDICINE

Tool for osteoarthritis risk prediction (TOARP) over 8 years using baseline clinical data, X-ray, and MRI: Data from the osteoarthritis initiative

(2017) Gabby B. Joseph et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Medial femur T 2 Z-scores predict the probability of knee structural worsening over 4-8 years: Data from the osteoarthritis initiative

(2017) Gabby B. Joseph et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the osteoarthritis initiative

(2017) Beth G. Ashinsky et al.   JOURNAL OF ORTHOPAEDIC RESEARCH

A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women

(2017) N. Lazzarini et al.   OSTEOARTHRITIS AND CARTILAGE

Knee osteoarthritis phenotypes and their relevance for outcomes: a systematic review

(2017) L.A. Deveza et al.   OSTEOARTHRITIS AND CARTILAGE

Identification of clinical phenotypes in knee osteoarthritis: a systematic review of the literature

(2016) A. Dell’Isola et al.   BMC MUSCULOSKELETAL DISORDERS

Clinical significance of worsening versus stable preradiographic MRI lesions in a cohort study of persons at higher risk for knee osteoarthritis

(2015) Leena Sharma et al.   ANNALS OF THE RHEUMATIC DISEASES

Osteoarthritis in the XXIst Century: Risk Factors and Behaviours that Influence Disease Onset and Progression

(2015) Giuseppe Musumeci et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

Distinct subtypes of knee osteoarthritis: data from the Osteoarthritis Initiative

(2015) Jan H. Waarsing et al.   RHEUMATOLOGY

Weight loss over 48 months is associated with reduced progression of cartilage T2 relaxation time values: Data from the osteoarthritis initiative

(2014) Arman T. Serebrakian et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Prediction model for knee osteoarthritis incidence, including clinical, genetic and biochemical risk factors

(2013) H J M Kerkhof et al.   ANNALS OF THE RHEUMATIC DISEASES

Estimating the Burden of Total Knee Replacement in the United States

(2013) Alexander M Weinstein et al.   JOURNAL OF BONE AND JOINT SURGERY-AMERICAN VOLUME

The Impact of Osteoarthritis in the United States

(2012) Louise Murphy et al.   AMERICAN JOURNAL OF NURSING

Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

(2012) Christopher J L Murray et al.   LANCET

Baseline mean and heterogeneity of MR cartilage T2 are associated with morphologic degeneration of cartilage, meniscus, and bone marrow over 3years – data from the Osteoarthritis Initiative

(2012) G.B. Joseph et al.   OSTEOARTHRITIS AND CARTILAGE

Association of magnetic resonance imaging-based knee cartilage T2 measurements and focal knee lesions with knee pain: Data from the Osteoarthritis Initiative

(2011) Thomas Baum et al.   ARTHRITIS CARE & RESEARCH

Evaluation of Cartilage Repair Tissue after Matrix-Associated Autologous Chondrocyte Transplantation Using a Hyaluronic-Based or a Collagen-Based Scaffold with Morphological MOCART Scoring and Biochemical T2 Mapping

(2010) Goetz Hannes Welsch et al.   AMERICAN JOURNAL OF SPORTS MEDICINE

Missing data imputation using statistical and machine learning methods in a real breast cancer problem

(2010) José M. Jerez et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Patellar Cartilage: T2 Values and Morphologic Abnormalities at 3.0-T MR Imaging in Relation to Physical Activity in Asymptomatic Subjects from the Osteoarthritis Initiative

(2009) Christoph Stehling et al.   RADIOLOGY