Orthopedics

The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs.

PURPOSE: To assess the ability of the Annalise Enterprise CXR Triage Trauma (Annalise AI Pty Ltd, Sydney, NSW, Australia) artificial intelligence model to identify vertebral compression fractures on chest radiographs and its potential to address undiagnosed osteoporosis and its treatment.

Research on the Motion Control Strategy of a Lower-Limb Exoskeleton Rehabilitation Robot Using the Twin Delayed Deep Deterministic Policy Gradient Algorithm.

The motion control system of a lower-limb exoskeleton rehabilitation robot (LLERR) is designed to assist patients in lower-limb rehabilitation exercises. This research designed a motion controller for an LLERR-based on the Twin Delayed Deep Deterministic policy gradient (TD3) algorithm to control the lower-limb exoskeleton for gait training in a staircase environment. Commencing with the establish...

An automated framework for pediatric hip surveillance and severity assessment using radiographs.

PURPOSE: Hip dysplasia is the second most common orthopedic condition in children with cerebral palsy (CP) and may result in disability and pain. The ...

SafeRPlan: Safe deep reinforcement learning for intraoperative planning of pedicle screw placement.

Spinal fusion surgery requires highly accurate implantation of pedicle screw implants, which must be conducted in critical proximity to vital structur...

Joint weight optimization for partial domain adaptation via kernel statistical distance estimation.

The goal of Partial Domain Adaptation (PDA) is to transfer a neural network from a source domain (joint source distribution) to a distinct target doma...

Socratic Artificial Intelligence Learning (SAIL): The Role of a Virtual Voice Assistant in Learning Orthopedic Knowledge.

OBJECTIVE: We hypothesized that learning through multiple sensory modalities would improve knowledge recall and recognition in orthopedic surgery resi...

Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement.

OBJECTIVES: This study aimed to assess the accuracy of machine learning (ML) models with feature selection technique in classifying cervical vertebral...

A Novel Bilateral Underactuated Upper Limb Exoskeleton for Post-Stroke Bimanual ADL Training.

This paper introduces a lightweight bilateral underactuated upper limb exoskeleton (UULE) designed to assist chronic stroke patients with distal joint...

Screening of genes co-associated with osteoporosis and chronic HBV infection based on bioinformatics analysis and machine learning.

OBJECTIVE: To identify HBV-related genes (HRGs) implicated in osteoporosis (OP) pathogenesis and develop a diagnostic model for early OP detection in ...

Machine learning for predicting duration of surgery and length of stay: A literature review on joint arthroplasty.

INTRODUCTION: In recent years, different factors such as population aging have caused escalating demand for hip and knee arthroplasty straining alread...

Deep learning constrained compressed sensing reconstruction improves high-resolution three-dimensional (3D) T2-weighted turbo spin echo magnetic resonance imaging (MRI) of the lumbar spine.

AIM: We sought to assess the image quality of three-dimensional (3D) T2-weighted (T2w) turbo spin echo (TSE) sequences with deep learning (DL)-constra...

Artificial intelligence and machine learning algorithms in diagnosis and therapy of the ankle joint.

The recent advancement of computational systems provides fast information exchange and the collection of large amounts of data. Growing number of thos...

Automatic 3D pelvimetry framework in CT images and its validation.

In the field of spinal pathology, sagittal balance of the spine is usually judged by the spatial structure and morphology of pelvis, which can be repr...

Deep Learning for Automated Classification of Hip Hardware on Radiographs.

PURPOSE: To develop a deep learning model for automated classification of orthopedic hardware on pelvic and hip radiographs, which can be clinically i...

Automated Three-Dimensional Imaging and Pfirrmann Classification of Intervertebral Disc Using a Graphical Neural Network in Sagittal Magnetic Resonance Imaging of the Lumbar Spine.

This study aimed to develop a graph neural network (GNN) for automated three-dimensional (3D) magnetic resonance imaging (MRI) visualization and Pfirr...

Artificial Intelligence-Based Surgery Support Model Using Intraoperative Radiographs for Assessing the Acetabular Component Angle.

BACKGROUND: This study aimed to develop an artificial intelligence-based surgical support model for assessing the acetabular component angle using int...

Squid-Inspired Anti-Salt Skin-Like Elastomers With Superhigh Damage Resistance for Aquatic Soft Robots.

Cephalopod skins evolve multiple functions in response to environmental adaptation, encompassing nonlinear mechanoreponse, damage tolerance property, ...

Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data.

UNLABELLED: Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-ROC = 0.968 for the prediction of moderate to sever...

Machine learning algorithm-based biomarker exploration and validation of mitochondria-related diagnostic genes in osteoarthritis.

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes ass...

MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images.

BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation free but previously has not been able to produce di...