IEEE transactions on bio-medical engineering
32031928
OBJECTIVE: Elucidating the role of structural mechanisms in the knee can improve joint surgeries, rehabilitation, and understanding of biped locomotion. Identification of key features, however, is challenging due to limitations in simulation and in-v...
Anterior cruciate ligament (ACL) injuries are common among athletes. Despite a successful return to sport (RTS) for most of the injured athletes, a significant proportion do not return to competitive levels, and thus RTS post ACL reconstruction still...
Journal of magnetic resonance imaging : JMRI
32715584
BACKGROUND: MRI is the most commonly used imaging method for diagnosing anterior cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time-intensive and depends on the clinical experience of the reader. An automated detection ...
Clinical orthopaedics and related research
32282466
BACKGROUND: Machine-learning methods such as the Bayesian belief network, random forest, gradient boosting machine, and decision trees have been used to develop decision-support tools in other clinical settings. Opioid abuse is a problem among civili...
OBJECTIVES: The aim of this study was to clinically validate a Deep Convolutional Neural Network (DCNN) for the detection of surgically proven anterior cruciate ligament (ACL) tears in a large patient cohort and to analyze the effect of magnetic reso...
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
32956803
PURPOSE: To (1) determine the diagnostic efficacy of artificial intelligence (AI) methods for detecting anterior cruciate ligament (ACL) and meniscus tears and to (2) compare the efficacy to human clinical experts.
This narrative "Year in Review" highlights a selection of articles published between January 2019 and April 2020, to be presented at the OARSI World Congress 2020 within the field of osteoarthritis (OA) imaging. Articles were obtained from a PubMed s...
IEEE journal of biomedical and health informatics
34003757
We propose an interpretable and lightweight 3D deep neural network model that diagnoses anterior cruciate ligament (ACL) tears from a knee MRI exam. Previous works focused primarily on achieving better diagnostic accuracy but paid less attention to p...