Orthopedics

Vertebral body insufficiency fractures: detection of vertebrae at risk on standard CT images using texture analysis and machine learning.

PURPOSE: To evaluate the diagnostic performance of bone texture analysis (TA) combined with machine ...

What Can We Learn from the RSNA Pediatric Bone Age Machine Learning Challenge?

Biomarkers of erosive arthritis in systemic lupus erythematosus: Application of machine learning models.

OBJECTIVE: Limited evidences are available on biomarkers to recognize Systemic Lupus erythematosus (...

The effects of short-term use of granulocyte colony-stimulating factor on bone metabolism in child cancer patients.

OBJECTIVE: The granulocyte colony-stimulating factor (G-CSF) is the most commonly used hematopoietic...

Evaluation of Effect of Glucosamine-Chondroitin Sulfate, Tramadol, and Sodium Hyaluronic Acid on Expression of Cytokine Levels in Internal Derangement of Temporomandibular Joint.

AIM: Evaluation of the effect of glucosamine-chondroitin combination, tramadol, and sodium hyaluroni...

Can low-frequency guided waves at the tibia paired with machine learning differentiate between healthy and osteopenic/osteoporotic subjects? A pilot study.

PURPOSE: Axial transmission quantitative acoustics (ax-QA) has shown to be a promising tool for asse...

Robot-assisted intravertebral augmentation corrects local kyphosis more effectively than a conventional fluoroscopy-guided technique.

OBJECTIVEIntravertebral augmentation (IVA) is a reliable minimally invasive technique for treating M...

Force Analysis and Evaluation of a Pelvic Support Walking Robot with Joint Compliance.

The force analysis of a pelvic support walking robot with joint compliance is discussed in this pape...

The RSNA Pediatric Bone Age Machine Learning Challenge.

Purpose The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challen...

A Convenient Non-harm Cervical Spondylosis Intelligent Identity method based on Machine Learning.

Cervical spondylosis (CS), a most common orthopedic diseases, is mainly identified by the doctor's j...

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.

BACKGROUND: Magnetic resonance imaging (MRI) of the knee is the preferred method for diagnosing knee...

eDRAM: Effective early disease risk assessment with matrix factorization on a large-scale medical database: A case study on rheumatoid arthritis.

Recently, a number of analytical approaches for probing medical databases have been developed to ass...

Comparison of the human-exosuit interaction using ankle moment and ankle positive power inspired walking assistance.

Previous ankle exoskeleton assistance techniques that were able to demonstrate metabolic reductions ...

Automated classification of benign and malignant lesions in F-NaF PET/CT images using machine learning.

PURPOSE: F-NaF PET/CT imaging of bone metastases is confounded by tracer uptake in benign diseases, ...

Robotically assisted long bone biopsy under MRI: cadaver study results.

RATIONALE AND OBJECTIVES: We have designed and constructed an MR-safe robot made entirely of nonmeta...

Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative.

We present a method for the automated segmentation of knee bones and cartilage from magnetic resonan...

Deep learning-based preoperative predictive analytics for patient-reported outcomes following lumbar discectomy: feasibility of center-specific modeling.

BACKGROUND CONTEXT: There is considerable variability in patient-reported outcome measures following...

Supervised learning for bone shape and cortical thickness estimation from CT images for finite element analysis.

Knowledge about the thickness of the cortical bone is of high interest for fracture risk assessment....

Robot-assisted percutaneous placement of K-wires during minimally invasive interventions of the spine.

To assess the accuracy and time requirements of image-guided percutaneous K-wire insertion in the s...

Prediction of early metastatic disease in experimental breast cancer bone metastasis by combining PET/CT and MRI parameters to a Model-Averaged Neural Network.

Macrometastases in bone are preceded by bone marrow invasion of disseminated tumor cells. This study...

Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs.

The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON) in fundus...