The American journal of sports medicine
Oct 7, 2016
BACKGROUND: It is increasingly recognized that biochemical abnormalities of the joint precede radiographic abnormalities of posttraumatic osteoarthritis (PTOA) by as much as decades. A growing body of evidence strongly suggests that the progression f...
PURPOSE: To assess the possible utility of machine learning for classifying subjects with and subjects without osteoarthritis using sodium magnetic resonance imaging data. Theory: Support vector machine, k-nearest neighbors, naïve Bayes, discriminant...
OBJECTIVES: This study aimed to evaluate the effectiveness of deep learning method for denoising and artefact reduction (AR) in zero echo time MRI (ZTE-MRI). Also, clinical applicability was evaluated by comparing image diagnosis to the temporomandib...
OBJECTIVES: This study aimed to clarify the performance of MRI-based deep learning classification models in diagnosing temporomandibular joint osteoarthritis (TMJ-OA) and to compare the developed diagnostic assistance with human observers.
BACKGROUND: People with osteoarthritis place a huge burden on society. Early diagnosis is essential to prevent disease progression and to select the best treatment strategy more effectively. In this study, the aim was to examine the diagnostic featur...
Emerging research shows that circular RNA (circRNA) plays a crucial role in the diagnosis, occurrence and prognosis of complex human diseases. Compared with traditional biological experiments, the computational method of fusing multi-source biologica...
BACKGROUND: Histology-based methods are commonly used in osteoarthritis (OA) research because they provide detailed information about cartilage health at the cellular and tissue level. Computer-based cartilage scoring systems have previously been dev...