BACKGROUND: Making surgery as less aggressive as possible is best for elderly patients with osteoporotic vertebral compression fractures (OVCFs). Recently, we attempted a more precise, minimally invasive, and robot-assisted kyphoplasty in our clinica...
Abnormalities and defects that can cause lumbar spinal stenosis often occur in the Intervertebral Disc (IVD) of the patient's lumbar spine. Their automatic detection and classification require an application of an image analysis algorithm on suitable...
Chronic back pain (CBP) is heterogenous and identifying sub-groups could improve clinical decision making. Machine learning can build upon prior sub-grouping approaches by using a data-driven approach to overcome clinician subjectivity, however, only...
BACKGROUND: Transforaminal epidural steroid injections (TFESI) are widely used to alleviate lumbosacral radicular pain. Knowledge of the therapeutic outcomes of TFESI allows clinicians to elucidate therapeutic plans for managing lumbosacral radicular...
PURPOSE: The purpose of this study was to develop and evaluate a deep learning model to detect bone marrow edema (BME) in sacroiliac joints and predict the MRI Assessment of SpondyloArthritis International Society (ASAS) definition of active sacroili...
BACKGROUND: Health-related patient-reported outcomes (HR-PROs) are crucial for assessing the quality of life among individuals experiencing low back pain. However, manual data entry from paper forms, while convenient for patients, imposes a considera...
The Journal of orthopaedic and sports physical therapy
38284363
To compare the accuracy of an artificial intelligence chatbot to clinical practice guidelines (CPGs) recommendations for providing answers to complex clinical questions on lumbosacral radicular pain. Cross-sectional study. We extracted recommendat...
Journal of orthopaedic surgery and research
39609923
BACKGROUND: Machine learning (ML) has been widely applied to predict the outcomes of numerous diseases. The current study aimed to develop a prognostic prediction model using machine learning algorithms and identify risk factors associated with resid...
OBJECTIVES: In axial spondyloarthritis (axSpA), early diagnosis is crucial, but diagnostic delay remains long and diagnostic criteria do not exist. We aimed to identify a diagnostic model that distinguishes patients with axSpA from patients without a...