Orthopedics

Editorial Commentary: Anterior Cruciate Ligament Patients Must Be Provided With Both Motivation and Tools to Continue Physical Therapy, Supervised or Independently, Beyond the Early Recovery Phase.

Given the current American health insurance environment, many patients do not access physical therapy in the mid and later stages of recovery from anterior cruciate ligament (ACL) reconstruction. This trend is well established in the literature and seems very unlikely to change in the future. While highly competitive athletes generally have year-round access to therapists and trainers to guide the...

Multitask learning for automatic detection of meniscal injury on 3D knee MRI.

Magnetic resonance imaging (MRI) of the knee is the recommended diagnostic method before invasive arthroscopy surgery. Nevertheless, interpreting knee MRI scans is a time-consuming process that is vulnerable to inaccuracies and inconsistencies. We proposed a multitask learning network MCSNet which efficiently introduces segmentation prior features and enhances classification results through multis...

Bioinspired design and validation of a soft robotic end-effector with integrated shape memory alloy-driven suction capabilities.

The exploration of adaptive robotic systems capable of performing complex tasks in unstructured environments, such as underwater salvage operations, p...

Advances in Artificial Intelligence for automated knee osteoarthritis classification using the IKDC system.

INTRODUCTION: Knee osteoarthritis is one of the most prevalent and debilitating musculoskeletal diseases, with a high incidence among the elderly popu...

A Human-Machine Joint Learning Framework to Boost Endogenous BCI Training.

Brain-computer interfaces (BCIs) provide a direct pathway from the brain to external devices and have demonstrated great potential for assistive and r...

A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults.

Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction...

Juxtaposition of bone age and sexual maturity rating of the Taiwanese population.

BACKGROUND: Bone age (BA) and sexual maturity rating (SMR) are crucial measures in assessing adolescent growth and development. However, studies speci...

Application of machine learning to identify risk factors for outpatient opioid prescriptions following spine surgery.

INTRODUCTION: Spine surgery is a common source of narcotic prescriptions and carries potential for long-term opioid dependence. As prescription opioid...

BMSMM-Net: A Bone Metastasis Segmentation Framework Based on Mamba and Multiperspective Extraction.

RATIONALE AND OBJECTIVES: Metastatic bone tumors significantly reduce patients' quality of life and expedite cancer spread. Traditional diagnostic met...

MicroRNA signature for early prediction of knee osteoarthritis structural progression using integrated machine and deep learning approaches.

OBJECTIVE: Conventional methodologies are ineffective in predicting the rapid progression of knee osteoarthritis (OA). MicroRNAs (miRNAs) show promise...

Automatic jawbone structure segmentation on dental CBCT images via deep learning.

OBJECTIVES: This study developed and evaluated a two-stage deep learning-based system for automatic segmentation of mandibular cortical bone, mandibul...

Cell quantification at the osteochondral interface from synchrotron radiation phase contrast micro-computed tomography images using a deep learning approach.

Osteochondral interface consists of two tissues: the calcified cartilage (CC) containing chondrocytes, and subchondral bone (SCB) containing osteocyte...

Developing predictive models for residual back pain after percutaneous vertebral augmentation treatment for osteoporotic thoracolumbar compression fractures based on machine learning technique.

BACKGROUND: Machine learning (ML) has been widely applied to predict the outcomes of numerous diseases. The current study aimed to develop a prognosti...

A Clinical Prediction Rule for Predicting the Health-related Quality of Life after 5 Months in Patients with Knee Osteoarthritis Undergoing Conservative Treatment.

OBJECTIVE: This study aimed to derive a clinical prediction rule (CPR) that can predict changes in health-related quality of life at 5 months for pati...

Bonevoyage: Navigating the depths of osteoporosis detection with a dual-core ensemble of cascaded ShuffleNet and neural networks.

BACKGROUND: Osteoporosis (OP) is a condition that significantly decreases bone density and strength, often remaining undetected until the occurrence o...

Concurrent validity and test reliability of the deep learning markerless motion capture system during the overhead squat.

Marker-based optical motion capture systems have been used as a cardinal vehicle to probe and understand the underpinning mechanism of human posture a...

Automatic 3-D Lamina Curve Extraction From Freehand 3-D Ultrasound Data Using Sequential Localization Recurrent Convolutional Networks.

Freehand 3-D ultrasound imaging is emerging as a promising modality for regular spine exams due to its noninvasiveness and affordability. The laminae ...

Categorization of Novel Research Ideas Regarding Adolescent Idiopathic Scoliosis Generated by Artificial Intelligence.

Background  The generation of innovative research ideas is crucial to advancing the field of medicine. As physicians face increasingly demanding clini...

Deep learning model for the automated detection and classification of central canal and neural foraminal stenosis upon cervical spine magnetic resonance imaging.

BACKGROUND: A deep learning (DL) model that can automatically detect and classify cervical canal and neural foraminal stenosis using cervical spine ma...

A Linear Rehabilitative Motion Planning Method with a Multi-Posture Lower-Limb Rehabilitation Robot.

In rehabilitation, physicians plan lower-limb exercises via linear guidance. Ensuring efficacy and safety, they design patient-specific paths, careful...