Latest AI and machine learning research in orthopedics for healthcare professionals.
ObjectiveThe traditional method of intraspinal anesthesia relies on surface anatomical landmarks for positioning, which is associated with a low accuracy rate. In addition, the procedure remains challenging, and the identification of anatomical structures is complex. This study aimed to develop an adaptive attention U-network to enhance the segmentation performance of spinal structures under ultra...
Autonomous robotic-assisted surgery (RAS) has emerged as a promising objective in biomedical technology, further enhanced by miniaturization toward microrobotic-assisted surgery (μ-RAS). This reduction in scale promises minimally invasive, partially or fully automated surgical procedures, with the potential to reduce patient recovery times, lower medical costs, and enable previously unavailable pr...
BACKGROUND: Artificial intelligence (AI)-powered virtual patient systems provide medical students with repeatable practice environments for history-ta...
OBJECTIVE: This study aimed to develop and validate an interpretable machine learning model using readily available biochemical indicators to predict ...
BACKGROUND: Osteoarthritis (OA) is a chronic degenerative joint disease characterized by the progressive deterioration of articular cartilage, signifi...
Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effe...
BACKGROUND: Dizziness and vertigo are common emergency department (ED) presentations, but only 2%-5% receive a serious diagnosis, such as stroke or tr...
Inflammatory rheumatic diseases (IRDs) represent a significant risk factor for cerebrovascular events, independent of traditional cardiovascular risk ...
PURPOSE: Joint space narrowing (JSN) in rheumatoid arthritis (RA) can progress even during clinical remission. Conventional imaging lacks sensitivity ...
EMG-based state estimation and prediction in human-machine interaction,biomechanics, and robotics applications is an emerging approach offering potent...
BACKGROUND: Scoliosis is a spinal disorder characterized by a three-dimensional (3D) deformity of the vertebral column. 3D ultrasound imaging has been...
Existing dietary patterns were not specifically designed to target osteoporosis and lack the precision required for effective prevention. We aimed to ...
This single-center retrospective study developed and internally validated a two-dimensional deep learning model based on cone-beam computed tomography...
Adolescent idiopathic scoliosis (AIS) surgery requires precise fusion segment selection and reliable prediction of postoperative alignment, yet curren...
BACKGROUND: Manual segmentation of prostate cancer metastases on PSMA PET/CT and SPECT/CT is time-consuming and poorly scalable, particularly in highl...
Event-related potential (ERP)-based brain-computer interface (BCI) systems are approaching sub-microvolt-level resolution, enabling detailed decoding ...
OBJECTIVE: The biomechanical properties of the lumbar spine is crucial for assisting the diagnosis, treatment, and prevention of spinal diseases. Trad...
Subject-specific finite-element analysis (FEA) models enable accurate simulation of vertebral biomechanics but are often time-consuming to construct a...
OBJECTIVES: To evaluate and compare the ability of three popular open-source artificial intelligence platforms to diagnose common trauma-related fract...
Purpose To develop and validate an end-to-end autonomous platform for the quantification and visualization of brain aneurysm and parent artery morphol...