Orthopedics

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI.

This study aimed to develop a deep learning (DL) algorithm for automated detection and localization of posterior ligamentous complex (PLC) injury in patients with acute thoracolumbar (TL) fracture on magnetic resonance imaging (MRI) and evaluate its diagnostic performance. In this retrospective multicenter study, using midline sagittal T2-weighted image with fracture (± PLC injury), a training dat...

Revolutionizing pediatric orthopedics: GPT-4, a groundbreaking innovation or just a fleeting trend?

A commentary on 'Clinical evaluation of the first semi-active total knee arthroplasty assisting robot made in China: a retrospective propensity score-matched cohort study'.

We were highly interested in the article entitled 'Clinical evaluation of the first semi-active total knee arthroplasty assisting robot made in China:...

ChatGPT in orthopedics: a narrative review exploring the potential of artificial intelligence in orthopedic practice.

The field of orthopedics faces complex challenges requiring quick and intricate decisions, with patient education and compliance playing crucial roles...

Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.

BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and posi...

Letter to the Editor Regarding "Prediction of Progressive Collapse in Osteoporotic Vertebral Fractures Using Conventional Statistics and Machine Learning".

Design and Analysis of an Upper Limb Rehabilitation Robot Based on Multimodal Control.

To address the rehabilitation needs of upper limb hemiplegic patients in various stages of recovery, streamline the workload of rehabilitation profess...

A Survey of Publicly Available MRI Datasets for Potential Use in Artificial Intelligence Research.

Artificial intelligence (AI) has the potential to bring transformative improvements to the field of radiology; yet, there are barriers to widespread c...

The invasiveness of robot-assisted total hip replacement is similar to that of conventional surgery.

Robot-assisted total hip arthroplasty (R-THA) is increasingly being performed throughout the world. The invasiveness of this operation is unknown. We ...

Unveiling Osteoporosis Through Radiomics Analysis of Hip CT Imaging.

RATIONALE AND OBJECTIVES: This study aims to investigate the use of radiomics analysis of hip CT imaging to unveil osteoporosis.

Multimodal Three-Dimensional Printing for Micro-Modulation of Scaffold Stiffness Through Machine Learning.

The ability to precisely control a scaffold's microstructure and geometry with light-based three-dimensional (3D) printing has been widely demonstrate...

Automatic segmentation and labelling of wrist bones in four-dimensional computed tomography datasets via deep learning.

This study developed a deep learning model for fully automatic segmentation and labelling of wrist bones from four-dimensional computed tomography (4D...

Analysis of learning the bimanual control of (tele)operating joint space controlled robotic arms with 4 degrees of freedom using the two-timescales power law of learning.

Training costs for operators of robotic arms in forestry and construction are high. A systematic analysis of skill development can help to make traini...

EMDL_m6Am: identifying N6,2'-O-dimethyladenosine sites based on stacking ensemble deep learning.

BACKGROUND: N6, 2'-O-dimethyladenosine (mAm) is an abundant RNA methylation modification on vertebrate mRNAs and is present in the transcription initi...

Effect of hip abduction assistance on metabolic cost and balance during human walking.

The use of wearable robots to provide walking assistance has rapidly grown over the past decade, with notable advances made in robot design and contro...

Cross-sectional area and fat infiltration of the lumbar spine muscles in patients with back disorders: a deep learning-based big data analysis.

PURPOSE: Validated deep learning models represent a valuable option to perform large-scale research studies aiming to evaluate muscle quality and quan...

Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning.

OBJECTIVE: To develop and evaluate a fully automated method based on deep learning and phantomless internal calibration for bone mineral density (BMD)...

A robot-aided visuomotor wrist training induces motor and proprioceptive learning that transfers to the untrained ipsilateral elbow.

BACKGROUND: Learning of a visuomotor task not only leads to changes in motor performance but also improves proprioceptive function of the trained join...

Joint triplet loss with semi-hard constraint for data augmentation and disease prediction using gene expression data.

The accurate prediction of patients with complex diseases, such as Alzheimer's disease (AD), as well as disease stages, including early- and late-stag...

Deep learning to automatically classify very large sets of preoperative and postoperative shoulder arthroplasty radiographs.

BACKGROUND: Joint arthroplasty registries usually lack information on medical imaging owing to the laborious process of observing and recording, as we...