Orthopedics

A machine learning approach to real-time calculation of joint angles during walking and running using self-placed inertial measurement units.

BACKGROUND: Inter-segment joint angles can be obtained from inertial measurement units (IMUs); however, accurate 3D joint motion measurement, which requires sensor fusion and signal processing, sensor alignment with segments and joint axis calibration, can be challenging to achieve.

A deep learning pipeline for systematic and accurate vertebral fracture reporting in computed tomography.

AIM: Spine fractures are a frequent and relevant diagnosis, but systematic documentation is time-consuming and sometimes overlooked. A deep learning pipeline for opportunistic fracture detection in computed tomography (CT) spine images of varying field-of-views is introduced.

Automated diagnosis and classification of temporomandibular joint degenerative disease via artificial intelligence using CBCT imaging.

OBJECTIVES: In this study, artificial intelligence (AI) techniques were used to achieve automated diagnosis and classification of temporomandibular jo...

Elephant-inspired tapered cable-driven hyper-redundant manipulator: design and performance analysis.

The cable-driven hyper-redundant manipulator (CDHM), distinguished by its high flexibility and adjustable stiffness, is extensively utilized in confin...

Optimising deep learning models for ophthalmological disorder classification.

Fundus imaging, a technique for recording retinal structural components and anomalies, is essential for observing and identifying ophthalmological dis...

AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study.

To evaluate the diagnostic accuracy of artificial intelligence (AI) assisted radiologists and standard double-reading in real-world clinical settings ...

Diagnosis and detection of bone fracture in radiographic images using deep learning approaches.

INTRODUCTION: Bones are a fundamental component of human anatomy, enabling movement and support. Bone fractures are prevalent in the human body, and t...

A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography.

Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties,...

Classifying tumour infiltrating lymphocytes in oral squamous cell carcinoma histopathology using joint learning framework.

Oral squamous cell carcinoma (OSCC) is the most common form of oral cancer, with increasing global incidence and have poor prognosis. Tumour-infiltrat...

The research progress of biologics in elderly-onset rheumatoid arthritis (EORA).

is a distinct subtype of characterized by heightened treatment challenges due to immune aging and the complexity of comorbidities. This review syste...

Stress radiography of medial knee instability provides a reliable correlation with the severity of injury and medial joint space opening-A robotic biomechanical cadaveric study.

PURPOSE: The medial collateral ligament (MCL), and posterior oblique ligament (POL) are the primary valgus stabilisers of the knee, and clinical exami...

Automatic skeletal maturity grading from pelvis radiographs by deep learning for adolescent idiopathic scoliosis.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional spine deformity governed of the spine. A child's Risser stage of skeletal maturity must b...

Utilizing deep learning for automatic segmentation of the cochleae in temporal bone computed tomography.

BackgroundSegmentation of the cochlea in temporal bone computed tomography (CT) is the basis for image-guided otologic surgery. Manual segmentation is...

Harnessing machine learning algorithms for the prediction and optimization of various properties of polylactic acid in biomedical use: a comprehensive review.

Machine learning (ML) has emerged as a transformative tool in various industries, driving advancements in key tasks like classification, regression, a...

Towards contrast-agnostic soft segmentation of the spinal cord.

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sectional area (CSA) for the diagnosis and monitoring...

Predicting lower body joint moments and electromyography signals using ground reaction forces during walking and running: An artificial neural network approach.

BACKGROUND: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground ...

Systematic application of saliency maps to explain the decisions of convolutional neural networks for glaucoma diagnosis based on disc and cup geometry.

This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simp...

Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study.

The hyoid bone has been identified as sexually dimorphic in various populations. The current study is a forerunner analysis that used three-dimensiona...

Automatic Vertical Root Fracture Detection on Intraoral Periapical Radiographs With Artificial Intelligence-Based Image Enhancement.

BACKGROUND/AIM: To explore transfer learning (TL) techniques for enhancing vertical root fracture (VRF) diagnosis accuracy and to assess the impact of...

Predicting fall parameters from infant skull fractures using machine learning.

When infants are admitted to the hospital with skull fractures, providers must distinguish between cases of accidental and abusive head trauma. Limite...