Orthopedics

Clinical validation of fully automated (peri-)articular tissue analysis for assessing osteoarthritis progression: A narrative review.

Numerous studies have presented fully automated techniques for assessing structural osteoarthritis (OA) progression, with recent work increasingly relying on deep learning (DL)-based methods. The objective of this narrative review was to summarize findings from studies comparing the validity of fully automated methods for assessing progression in (peri-) articular joint tissues with reference meas...

Performance of ChatGPT versus spine surgeons as an emergency department spine call consultant.

BACKGROUND: Large language models (LLMs) like ChatGPT are increasingly being recognized as credible tools for use across diverse healthcare settings. While artificial intelligence (AI) use has previously been evaluated in emergency medicine, its use in subspecialty care - particularly spine surgery - remains underexplored. This study evaluates the clinical accuracy, management appropriateness, com...

Identification and validation of immune-related biomarkers in osteoarthritis via integrated bioinformatics and experimental approaches.

UNLABELLED: Knee osteoarthritis (OA) is a prevalent degenerative joint disease and a leading cause of disability worldwide. While traditionally consid...

Evaluating the cost-effectiveness of artificial intelligence-enhanced osteoporosis screening in men and women using routine chest radiographs in South Korea.

South Korea, now a "super-aged" society, faces a rising burden of fragility fractures, yet underdiagnosis remains a major barrier, with limited DXA ac...

Diagnosis of shoulder dislocation on AP radiographs: A comparative analysis of diagnostic performance between orthopedic surgeons, emergency physicians, and ChatGPT models.

OBJECTIVE: This study aimed to evaluate the diagnostic performance of ChatGPT in identifying acute shoulder dislocations and to compare its accuracy w...

Factors associated with rapid spinal radiographic progression in patients with axial spondyloarthritis: A hospital-based retrospective cohort study with mSASSS scoring using deep learning model.

OBJECTIVE: To identify associated and protective factors of rapid spinal radiographic progression in axial spondyloarthritis (axSpA) using artificial ...

Synthetic computed tomography from magnetic resonance imaging: An editorial on deep learning approaches for hip and knee image translation.

This editorial provides a concise overview of synthetic computed tomography (CT) generation from magnetic resonance imaging (MRI) for musculoskeletal ...

Thigh Muscle Changes in the ACL-Deficient Knee: A 4-Year Longitudinal MRI Study of 1,207 Patients.

BACKGROUND: Anterior cruciate ligament (ACL) injuries may lead to long-term neuromuscular and structural adaptations in thigh muscles. Although quadri...

Computer-vision based recognition of cervical spine stabilization during trauma resuscitation.

BACKGROUND: Cervical spine (c-spine) injuries can lead to significant disability and mortality. Although stabilization is the primary management for s...

AI-Driven CT-MRI Image Fusion and Segmentation for Automatic Preoperative Planning of ACL Reconstruction: Development and Application.

BACKGROUND: The goals of this study were to develop an artificial intelligence (AI)-driven automated preoperative planning system for anterior cruciat...

Mri-based habitat and peritumoral radiomics for predicting the proliferative activity of stromal cells in giant cell tumor of bone.

PURPOSE: This study aims to explore the feasibility of MRI-based habitat and peritumoral radiomics for predicting the proliferative activity of stroma...

Deep learning for pediatric femoral neck fracture detection in a multicenter study.

Pediatric femoral neck fractures (FNFs) are uncommon but may result in severe complications if undiagnosed. This study developed a deep learning model...

Graph based multi-agent reinforcement learning with evolutionary population for cooperation.

In fully cooperative environments, agents aim to learn a joint policy to achieve a shared goal. However, existing Multi-Agent Reinforcement Learning (...

Deep Learning in Vertebral Fracture Detection: Systematic Review and Meta-analysis of Subject- vs. Vertebra-Level Approaches.

RATIONALE AND OBJECTIVES: To provide a context-aware evaluation of deep learning algorithms for vertebral fracture detection by disentangling subject-...

Saccade Tasks: A Noninvasive Approach for Predicting Postoperative Delirium in Elderly Arthroplasty Patients.

BACKGROUND: Postoperative delirium (POD) is a prevalent complication in elderly surgical patients. It is associated with long-term cognitive impairmen...

Utilizing Optimized Mixed-Order Relation-Aware Recurrent Neural Network for Metacarpophalangeal Rheumatoid Arthritis Grading via Ultrasound Images.

The diagnostic problem of grading evaluation of ultrasonic images of Metacarpophalangeal rheumatoid arthritis (RA) is mostly dependent on the skills o...

Joint modelling of brain and behaviour dynamics with artificial intelligence.

Artificial intelligence has created tremendous advances for many scientific and engineering applications. In this Review, we synthesize recent advance...

Joint Associations of Type D Personality and Allostatic Load With Coronary Artery Disease in Type 2 Diabetes: Evaluating the Role of Allostatic Load.

OBJECTIVE: This study aimed to (1) evaluate and compare the independent associations and predictive strength of type D personality and allostatic load...

Programmable materials: A comprehensive review on shape memory polymers for orthopedic applications.

Shape memory polymers (SMP) are smart, active polymers, which can significantly change their properties by external stimuli such as heat or temperatur...

Bot vs. doc-who is better at reading proximal humerus fracture x-rays?

BACKGROUND: Artificial intelligence is becoming increasingly utilized as a source of convenient, efficient, and cost-effective information. Considerin...