Orthopedics

Can Patients Rely on ChatGPT to Answer Hand Pathology-Related Medical Questions?

BACKGROUND: In recent years, ChatGPT has become a popular source of information online. Physicians need to be aware of the resources their patients are using to self-inform of their conditions. This study investigates physician-graded accuracy and completeness of ChatGPT regarding various questions patients are likely to ask the artificial intelligence (AI) system concerning common upper limb orth...

YOLOX-SwinT algorithm improves the accuracy of AO/OTA classification of intertrochanteric fractures by orthopedic trauma surgeons.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification.

Fast SPECT/CT planar bone imaging enabled by deep learning enhancement.

BACKGROUND: The application of deep learning methods in rapid bone scintigraphy is increasingly promising for minimizing the duration of SPECT examina...

Age and medial compartmental OA were important predictors of the lateral compartmental OA in the discoid lateral meniscus: Analysis using machine learning approach.

PURPOSE: The objective of this study was to develop a machine learning model that would predict lateral compartment osteoarthritis (OA) in the discoid...

A Fast Online Elastic-Spine-Based Stiffness Adjusting Mechanism for Fishlike Swimming.

Fish tunes fishtail stiffness by coordinating its tendons, muscles, and other tissues to improve swimming performance. For robotic fish, achieving a f...

Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults.

BACKGROUND: Computed tomography (CT) body compositions reflect age-related metabolic derangements. We aimed to develop a multi-outcome deep learning m...

Multivariate analysis of the kinematics of an upper limb rehabilitation robot.

The purpose of this work is to present a multivariate analysis of the kinematics of an upper limb rehabilitation robot. Comparing multiple concepts o...

Unveiling the link between lactate metabolism and rheumatoid arthritis through integration of bioinformatics and machine learning.

Rheumatoid arthritis (RA) is a persistent autoimmune condition characterized by synovitis and joint damage. Recent findings suggest a potential link t...

Machine learning and weighted gene co-expression network analysis identify a three-gene signature to diagnose rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is a systemic immune-related disease characterized by synovial inflammation and destruction of joint cartilage. ...

Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations.

Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots ...

Artificial intelligence diagnostic accuracy in fracture detection from plain radiographs and comparing it with clinicians: a systematic review and meta-analysis.

PURPOSE: Fracture detection is one of the most commonly used and studied aspects of artificial intelligence (AI) in medicine. In this systematic revie...

Artificial Intelligence Assistance for the Measurement of Full Alignment Parameters in Whole-Spine Lateral Radiographs.

BACKGROUND: Measuring spinal alignment with radiological parameters is essential in patients with spinal conditions likely to be treated surgically. T...

Multimodality Fusion Strategies in Eye Disease Diagnosis.

Multimodality fusion has gained significance in medical applications, particularly in diagnosing challenging diseases like eye diseases, notably diabe...

A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.

BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. ...

The Classification of Lumbar Spondylolisthesis X-Ray Images Using Convolutional Neural Networks.

We aimed to develop and validate a deep convolutional neural network (DCNN) model capable of accurately identifying spondylolysis or spondylolisthesis...

Thrombosed Persistent Median Artery with Coexisting Bifid Median Nerve in a Robotic Arthroplasty Surgeon: A Case Report.

CASE: A 47-year-old orthopaedic surgeon presented with acute volar left wrist pain. He performed over 250 robot-assisted knee arthroplasties each year...

Gait Alterations and Association With Worsening Knee Pain and Physical Function: A Machine Learning Approach With Wearable Sensors in the Multicenter Osteoarthritis Study.

OBJECTIVE: The objective of this study was to identify gait alterations related to worsening knee pain and worsening physical function, using machine ...

Robot-assisted anterior cruciate ligament reconstruction based on three-dimensional images.

Background Tunnel placement is a key step in anterior cruciate ligament (ACL) reconstruction. The purpose of this study was to evaluate the accuracy o...

Identification of biomarkers and immune infiltration characterization of lipid metabolism-associated genes in osteoarthritis based on machine learning algorithms.

Osteoarthritis (OA) is a prevalent degenerative condition commonly observed in the elderly, leading to consequential disability. Despite notable advan...

An artificial intelligence-based model for predicting reproductive toxicity of bisphenol analogues mixtures to the rotifer Brachionus calyciflorus.

The joint toxicity effects of mixtures, particularly reproductive toxicity, one of the main causes of aquatic ecosystem degradation, are often overloo...