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Scapula

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Shoulder motion assistance using a single-joint Hybrid Assistive Limb robot: Evaluation of its safety and validity in healthy adults.

Journal of orthopaedic surgery (Hong Kong)
PURPOSES: To evaluate the feasibility of using the single-joint Hybrid Assistive Limb robot (HAL) to assist with shoulder flexion-extension in healthy adults, and to assess the capacity of the HAL to analyze the bioelectrical signals of muscle activi...

Machine learning algorithms for predicting scapular kinematics.

Medical engineering & physics
The goal of this study was to develop and validate a non-invasive approach to estimate scapular kinematics in individual patients. We hypothesized that machine learning algorithms could be developed using motion capture data to accurately estimate dy...

Deep learning classification of shoulder fractures on plain radiographs of the humerus, scapula and clavicle.

PloS one
In this study, we present a deep learning model for fracture classification on shoulder radiographs using a convolutional neural network (CNN). The primary aim was to evaluate the classification performance of the CNN for proximal humeral fractures (...

Automatic quantification of scapular and glenoid morphology from CT scans using deep learning.

European journal of radiology
OBJECTIVES: To develop and validate an open-source deep learning model for automatically quantifying scapular and glenoid morphology using CT images of normal subjects and patients with glenohumeral osteoarthritis.

Machine learning insights into scapular stabilization for alleviating shoulder pain in college students.

Scientific reports
Non-specific shoulder pain is a common musculoskeletal condition, especially among college students, and it can have a negative impact on the patient's life. Therapists have used scapular stabilization exercises (SSE) to enhance scapular control and ...

Deep learning algorithms enable MRI-based scapular morphology analysis with values comparable to CT-based assessments.

Scientific reports
Scapular morphological attributes show promise as prognostic indicators of retear following rotator cuff repair. Current evaluation techniques using single-slice magnetic-resonance imaging (MRI) are, however, prone to error, while more accurate compu...

An accelerated deep learning model can accurately identify clinically important humeral and scapular landmarks on plain radiographs obtained before and after anatomic arthroplasty.

International orthopaedics
PURPOSE: Accurate identification of radiographic landmarks is fundamental to characterizing glenohumeral relationships before and sequentially after shoulder arthroplasty, but manual annotation of these radiographs is laborious. We report on the use ...

Cascade learning in multi-task encoder-decoder networks for concurrent bone segmentation and glenohumeral joint clinical assessment in shoulder CT scans.

Artificial intelligence in medicine
Osteoarthritis is a degenerative condition that affects bones and cartilage, often leading to structural changes, including osteophyte formation, bone density loss, and the narrowing of joint spaces. Over time, this process may disrupt the glenohumer...

Innovative diagnostic framework for shoulder instability: a narrative review on machine learning-enhanced scapular dyskinesis assessment in sports injuries.

European journal of medical research
A common shoulder problem that significantly detracts from patients' quality of life is shoulder instability (SI). Abnormal scapular positioning and movement are closely associated with rotator cuff injuries and SI, as shown by several studies. The a...