Orthopedics

Comparison of ChatGPT's Diagnostic and Management Accuracy of Foot and Ankle Bone-Related Pathologies to Orthopaedic Surgeons.

INTRODUCTION: The steep rise in utilization of large language model chatbots, such as ChatGPT, has spilled into medicine in recent years. The newest version of ChatGPT, ChatGPT-4, has passed medical licensure examinations and, specifically in orthopaedics, has performed at the level of a postgraduate level three orthopaedic surgery resident on the Orthopaedic In-Service Training Examination questi...

The Application of Artificial Intelligence in Spine Surgery: A Scoping Review.

BACKGROUND: A comprehensive review on the application of artificial intelligence (AI) within spine surgery as a specialty remains lacking.

Accelerometer-derived classifiers for early detection of degenerative joint disease in cats.

Decreased mobility is a clinical sign of degenerative joint disease (DJD) in cats, which is highly prevalent, with 61 % of cats aged six years or olde...

The Role of ChatGPT in osteoporosis management: a comparative analysis with clinical expertise.

UNLABELLED: This study evaluates the role of ChatGPT in osteoporosis management, demonstrating 91% diagnostic accuracy and significantly faster respon...

Effect of esketamine on the EC of remifentanil for suppression of choking cough during extubation.

Choking cough during awakening from anesthesia is common (15%-94%) and can cause severe discomfort and complications, especially in neck surgery. This...

Predicting ground reaction forces and center of pressures from kinematic data in crutch gait based on LSTM.

Crutches are of extensive applications in the field of rehabilitation. Comprehensively analyzing the ground reaction forces (GRFs) on both crutches an...

Molecular Subtypes and Immune Microenvironment Characterization of the Annulus Fibrosus in Intervertebral Disc Degeneration: Insights From Translation Factor-Related Gene Analysis.

OBJECTIVE: This study aims to examine the role of translation factors (TF) in intervertebral disc degeneration (IVDD) and to evaluate their clinical r...

Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.

Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study, we developed and validated a flexible, open-acce...

Parametric-MAA: fast, object-centric avoidance of metal artifacts for intraoperative CBCT.

PURPOSE: Metal artifacts remain a persistent issue in intraoperative CBCT imaging. Particularly in orthopedic and trauma applications, these artifacts...

Assessing the performance of ChatGPT-4o on the Turkish Orthopedics and Traumatology Board Examination.

OBJECTIVES: This study aims to assess the overall performance of ChatGPT version 4-omni (GPT-4o) on the Turkish Orthopedics and Traumatology Board Exa...

MIST: An interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis.

Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provides a powerful approach for in-depth T cell immune ...

Information Extraction from Lumbar Spine MRI Radiology Reports Using GPT4: Accuracy and Benchmarking Against Research-Grade Comprehensive Scoring.

: This study aimed to create a pipeline for standardized data extraction from lumbar-spine MRI radiology reports using a large language model (LLM) an...

TransformDDI: The Transformer-Based Joint Multi-Task Model for End-to-End Drug-Drug Interaction Extraction.

Drug-Drug Interactions (DDI) identification is a part of the drug safety process, that focuses at avoiding potential adverse drug effects that can lea...

Redefining Value in Orthopedic Surgery.

Value-based health care is a commonly used term that merits a strong understanding from the orthopedic surgeon given its importance in orthopedic pati...

Evolutionary learning in neural networks by heterosynaptic plasticity.

Training biophysical neuron models provides insights into brain circuits' organization and problem-solving capabilities. Traditional training methods ...

A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features.

OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classification being crucial for proper treatment planning. Stu...

Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.

Chronic kidney disease-mineral bone disorder is a common complication in patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD...

Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value.

PURPOSE: To evaluate the usefulness of radiomics features extracted from ultrasonographic images in diagnosing and predicting the severity of knee ost...

Therapeutic potential of allosteric HECT E3 ligase inhibition.

Targeting ubiquitin E3 ligases is therapeutically attractive; however, the absence of an active-site pocket impedes computational approaches for ident...

Deep Learning-Based Reconstruction for Accelerated Cervical Spine MRI: Utility in the Evaluation of Myelopathy and Degenerative Diseases.

BACKGROUND AND PURPOSE: Deep learning (DL)-based reconstruction enables improving the quality of MR images acquired with a short scan time. We aimed t...