Orthopedics

Expert Evaluation of the Perceived Accuracy, Relevance, and Safety of Large Language Model-Generated Patient Information in Geriatrics: Cross-Condition Study.

BACKGROUND: Large language models (LLMs) are increasingly used to generate patient-oriented medical information. In geriatrics, such information must balance accuracy, relevance, and safety, as older adults may be particularly susceptible to misleading or harmful advice. However, systematic evaluations of expert perceptions across multiple geriatric conditions remain limited. OBJECTIVE: This study...

High-Resolution 2D versus 3D Lumbar Spine MRI Optimized with a Deep Learning Reconstruction Algorithm and Prototype Conformal Coil.

BACKGROUND AND PURPOSE: Lumbar spine MRI is predominantly performed using 2D FSE sequences. 3D FSE sequences offer potential advantages over 2D, especially with recent advances in deep-learning reconstruction (DLR) and the use of conformal high-density coil arrays to improve the SNR. This study aimed to compare image quality and diagnostically relevant differences between 2D and 3D lumbar spine pr...

Interpretable machine learning for postoperative nausea and vomiting prediction in elderly orthopedic patients: a comparative study.

BACKGROUND: Postoperative nausea and vomiting (PONV) prolongs hospitalization and reduces patient satisfaction. Identifying high-risk elderly patients...

Identification of potential biomarkers for osteoporosis and chronic kidney disease through bioinformatics and machine learning algorithm.

OBJECTIVE: The purpose of this study is to identify hub genes associated with both osteoporosis (OP) and chronic kidney disease (CKD) through bioinfor...

Artificial intelligence predictions of knee kinematics, kinetics, and internal biomechanics during walking in people with knee osteoarthritis: A systematic review and meta-analysis.

This review synthesizes current literature on the use of artificial intelligence (AI) to predict knee biomechanics during walking in people with knee ...

Assessment of the Performance of Siemens Scopio Digital Morphology on Bone Marrow Aspirates in Onco-Hematology.

OBJECTIVES: Digital morphology (DM) systems assisted by artificial intelligence are increasingly being introduced into hematology laboratories; howeve...

Generalist Large-Language Models for Spine Imaging Diagnostics: An Early Analysis of Detection Performance for Scoliosis and Lumbar Stenosis.

BACKGROUND: Web-based large language models (LLMs) are increasingly used by patients for medical self-assessment, but their efficacy in spine imaging ...

The Use of Statistical Shape and Appearance Modelling for Predicting Osteoporotic Fracture Risk.

PURPOSE OF REVIEW: Osteoporotic fractures remain a major cause of morbidity and mortality worldwide. Current clinical assessment metrics (e.g., bone m...

Interpretable LightGBM model for predicting postoperative gastrointestinal hemorrhage in elderly hip fracture patients: leveraging systemic inflammation and medication exposures for personalized risk stratification.

BACKGROUND: Postoperative gastrointestinal (GI) bleeding is a serious complication after hip fracture surgery in older adults, yet perioperative risk ...

Diagnostic performance of artificial intelligence for identification of cervical spine fractures: a systematic review and meta-analysis.

PURPOSE: This meta-analysis aimed to evaluate how effectively artificial intelligence (AI) models can diagnose cervical spine fractures. METHODS: A sy...

Fiducial Confidence Intervals for Agreement Measures Among Raters Under a Generalized Linear Mixed Effects Model.

A generalization of the classical concordance correlation coefficient (CCC) is considered under a three-level design where multiple raters rate every ...

Deep Learning-Based Comparison of Knee Minimum Joint Space Width in Patients with Rheumatoid Arthritis and Osteoarthritis Before Total Knee Arthroplasty.

OBJECTIVE: While osteoarthritis (OA) and rheumatoid arthritis (RA) can necessitate total knee arthroplasty (TKA), the mechanisms and radiographic patt...

A biomechanical-constrained temporal learning framework for lightweight skeleton-based exercise recognition.

The recognition of exercises using skeletal pose sequences is a significant fitness technology, rehabilitation monitoring, and sports analytics. Never...

Feasibility of No-Code Deep Learning for Diagnosing Bone Metastasis in Bone Scans: A Comparative Study of Teachable Machine and ResNet.

This study explored the feasibility of developing a model that can diagnose positive and negative bone metastasis from bone scan images using Teachabl...

SIRT1 Downregulation by Advanced Glycation End Products Activates RANKL-Dependent Osteoclast Signaling and Drives Chondrocyte Senescence During Osteoarthritis Development.

Advanced glycation end products (AGEs) accumulate with aging and metabolic stress and are increasingly implicated in osteoarthritis (OA) pathology. Ho...

Deep Learning Reconstruction Enables Diagnostic-Quality 0.4T Knee and Spine MRI in One-Third of the Time.

There has been a growing interest in low-field MRI due to its lower costs, enabling an increase in accessibility of MRI worldwide. Long scan times are...

Development and Internal Validation of a Machine Learning Model for Predicting Long-Term Opioid Therapy After Hip Fracture Surgery in Older, Opioid-Naïve Adults.

BACKGROUND: Long-term opioid therapy (LTOT) after hip fracture surgery is a common postoperative complication associated with adverse outcomes, yet to...

Spectral deep learning-based patient and bowtie scatter correction for clinical photon-counting CT.

BACKGROUND: The presence of scatter in computed tomography degrades image quality, and can be caused by the patient and by other components in the bea...

Geometric Transformation Algorithm for Acetabular Cup Orientation: Converting 2D Radiographic Projections to 3D Spatial Positioning.

BACKGROUND/AIM: Hip replacement is one of the most common and successful surgeries of our time. However, with increasing numbers of total hip arthropl...

Unsupervised Machine Learning Drives Dynamic Alignment Classification In Navigated Total Knee Arthroplasty.

BACKGROUND: Current classifications used for total knee arthroplasty (TKA) are static and fail to capture the dynamic behavior of the limb during gait...