Orthopedics

Hip Hiking Gait Improvement with Electrohydraulic Robotic Knee: Preliminary Results.

Individuals with Transfemoral Amputation (TFA) usually exhibit hip hiking walking with passive prost...

Single Bone Modeler: deep learning bone segmentation for cone-beam CT.

The accurate segmentation and modeling of bones play a crucial role in diagnosis and surgical planni...

Ultrasound for Automated Classification of Full-Thickness Rotator Cuff Tendon Tears using Deep Learning.

Rotator cuff tendon tears, the most common shoulder injuries, are typically diagnosed mainly through...

An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adoles...

Vertebrae Segmentation with Generative Adversarial Networks for Automatic Cobb Angle Measurement.

Scoliosis is a lateral deformity of the spine, usually diagnosed in patients with a Cobb angle (CA) ...

EUFormer: Learning Driven 3D Spine Deformity Assessment with Orthogonal Optical Images.

In clinical settings, the screening, diagnosis, and monitoring of adolescent idiopathic scoliosis (A...

A Three-Stage Semi-Supervised Learning Approach to Spine Image Segmentation.

Spine segmentation in computed tomography (CT) images is critical for automatic analysis, especially...

Rapid screening of acute promyelocytic leukaemia in daily batch specimens: A novel artificial intelligence-enabled approach to bone marrow morphology.

Can artificial intelligence techniques help clinicians assess and treat patients with bone fractures?

Interobserver Agreement and Performance of Concurrent AI Assistance for Radiographic Evaluation of Knee Osteoarthritis.

Background Due to conflicting findings in the literature, there are concerns about a lack of objecti...

Automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning.

The aim of this study was to construct a classification model for the automatic diagnosis of pediatr...

Assessing the Efficacy of Synthetic Optic Disc Images for Detecting Glaucomatous Optic Neuropathy Using Deep Learning.

PURPOSE: Deep learning architectures can automatically learn complex features and patterns associate...

Explainable Machine Learning Model to Predict Overall Survival in Patients Treated With Palliative Radiotherapy for Bone Metastases.

PURPOSE: The estimation of prognosis and life expectancy is critical in the care of patients with ad...

Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial.

Background Diagnosing osteoporosis is challenging due to its often asymptomatic presentation, which ...

AI and Chest Radiographs: A Dawning Era in Osteoporosis Screening.

[Deep transfer learning radiomics model based on temporal bone CT for assisting in the diagnosis of inner ear malformations].

To evaluate the diagnostic efficacy of traditional radiomics, deep learning, and deep learning radio...

Force/position tracking control of fracture reduction robot based on nonlinear disturbance observer and neural network.

BACKGROUND: For the fracture reduction robot, the position tracking accuracy and compliance are affe...

[Minimally invasive intelligent innovative technologies in foot and ankle surgery: development status and prospects].

The rapid development of technology has ushered in a new era of minimally invasive and intelligent s...

Deep learning-based spinal canal segmentation of computed tomography image for disease diagnosis: A proposed system for spinal stenosis diagnosis.

BACKGROUND: Lumbar disc herniation was regarded as an age-related degenerative disease. Nevertheless...

Enhanced osteoporotic fracture prediction in postmenopausal women using Bayesian optimization of machine learning models with genetic risk score.

This study aimed to enhance the fracture risk prediction accuracy in major osteoporotic fractures (M...

PallorMetrics: Software for Automatically Quantifying Optic Disc Pallor in Fundus Photographs, and Associations With Peripapillary RNFL Thickness.

PURPOSE: We sough to develop an automatic method of quantifying optic disc pallor in fundus photogra...