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Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks.

, , , and . ICPR, page 1195-1200. IEEE, (2016)

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An Interactive Segmentation Tool for Quantifying Fat in Lumbar Muscles using Axial Lumbar-Spine MRI., , , , , , and . CoRR, (2016)Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks., , , and . ICPR, page 1195-1200. IEEE, (2016)Automatic detection, extraction and analysis of unrestrained gait using a wearable sensor system., , , and . EMBC, page 2034-2037. IEEE, (2015)Automatically detecting asymmetric running using time and frequency domain features., , , , , , and . BSN, page 1-6. IEEE, (2015)MedFit: A Mobile Application for Patients in CVD Recovery., , , , , , , and . MMHealth@MM, page 93-96. ACM, (2017)Recognition and Repetition Counting for Local Muscular Endurance Exercises in Exercise-Based Rehabilitation: A Comparative Study Using Artificial Intelligence Models., , and . Sensors, 20 (17): 4791 (2020)A virtual coaching environment for improving golf swing technique., , , and . SMVC@MM, page 51-56. ACM, (2010)A Deep Learning Model for Exercise-Based Rehabilitation Using Multi-channel Time-Series Data from a Single Wearable Sensor., , and . MobiHealth, volume 362 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 104-115. Springer, (2020)PATHway: Decision Support in Exercise Programmes for Cardiac Rehabilitation., , , , , , , , , and . pHealth, volume 224 of Studies in Health Technology and Informatics, page 40-45. IOS Press, (2016)Feature Learning to Automatically Assess Radiographic Knee Osteoarthritis Severity., , , and . CoRR, (2019)