Orthopedics

The Influence of the COVID-19 Pandemic on Current Teaching Methods, Training, and Perception among Romanian Surgery-Oriented Students: Observational, Cross-Sectional Multicentric Study.

BACKGROUND: The COVID-19 pandemic prompted rapid changes in medical education, accelerating the adoption of online and distance learning methods as alternatives to traditional teaching. While these approaches offered logistical advantages, students worldwide reported significant limitations, particularly in terms of motivation, clinical exposure, and hands-on skill acquisition. Despite increased u...

Artificial intelligence models for osteoporosis risk prediction in postmenopausal women with CKD: A cross-sectional analysis of NHANES 2005 to 2018.

Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal women with chronic kidney disease remains limited. We sought to develop and interpret an explainable AI model specifically for identifying low bone mass (LBM) or OP in this vulnerable group. Using data from the National Health and Nutrition Examination S...

Scalable and Robust Artificial Intelligence for Spine Alignment Assessment: Multicenter Study Enabled by Real-Time Data Transformation.

BACKGROUND: Artificial intelligence (AI) has shown promise for automating spinal alignment assessment in adolescent idiopathic scoliosis (AIS). Howeve...

Artificial Intelligence as a Catalyst for Value-Based Health Insurance in the United States: Narrative Review and Policy Perspective.

The United States health insurance system is at a critical crossroads. Inflating costs, fragmented care, and administrative inefficiencies have reveal...

Comparing large language models and human experts in interpreting MRI reports for personalized patient education.

RATIONALE AND OBJECTIVES: Knee osteoarthritis (OA) is a prevalent global condition. While MRI guides clinical decisions, its technical complexity hind...

Advancing diagnostic equity through artificial intelligence chest radiograph screening for osteoporosis in Asian populations.

Early identification of abnormal bone mineral density (BMD) through opportunistic screening is critical for preventing osteoporotic fractures. We vali...

Enhancing automated fracture detection in paediatric wrist X-rays with paired and unpaired cast suppression methods.

PURPOSE: Casts in follow-up wrist X-rays reduce diagnostic image quality, complicating the assessment of fracture healing. This study developed cast s...

DeepSeek-R1 performance in fusion planning of adolescent idiopathic scoliosis: A preliminary study.

BACKGROUND: Surgical planning for adolescent idiopathic scoliosis (AIS) is complex. Large language models (LLMs) like DeepSeek Reasoning Model R1 (Dee...

Predicting self-image satisfaction after adult spinal deformity surgery: a machine learning approach using patient phenotypes.

PURPOSE: To characterize the evolution of the Self-Image (SI) domain of the Scoliosis Research Society-22 item questionnaire (SRS-22) in adult spinal ...

Identification and validation of NETs-associated biomarkers in osteoporosis with diabetes.

Osteoporosis and diabetes represent major global public health challenges. Neutrophil extracellular traps (NETs) serve as key components of the innate...

Canine gait analysis using inertial sensors and deep learning for orthopedic and neurological disorders.

Canine gait analysis using wearable inertial sensors is gaining attention in veterinary clinical settings, as it provides valuable insights into a ran...

A framework of hybrid deep learning and nature-inspired algorithms for accurate multi-class fundus disease classification.

Fundus imaging is an essential technique for detecting anatomical changes indicative of various ophthalmological diseases. These alterations-including...

Predicting skeletal fluorosis severity using machine learning across diverse fluoride-exposed populations in China.

Skeletal fluorosis (SF) is a chronic metabolic bone disease resulting from long-term excessive fluoride exposure, affecting millions worldwide. Conven...

FAD-MIL: a weakly supervised fracture detection model based on X-ray images.

Fractures are among the most common presentations to emergency and orthopedic services, yet radiograph interpretation remains inconsistent, particular...

High-Speed Instance Segmentation for Endoscopic Spine Surgery: Multicenter Validation and Inference Speed Evaluation.

Study DesignRetrospective Multicenter Cohort Study.ObjectivesTo develop and validate an AI-based high-speed multi-class instance segmentation system f...

Integration of detection and tracking networks for automated rib multiplanar reconstruction: a feasibility study for fracture diagnosis.

OBJECTIVE: Rib fractures are common yet time-consuming to diagnose. This study explores automation via multiplanar reconstruction and intelligent dete...

Minimally invasive spine surgery: current advantages, limitations, and future directions.

Minimally invasive spine surgery (MISS), supported by advancements in endoscopic systems, tubular retractors, lateral access corridors, image-guided n...

Patient Perceptions of Artificial Intelligence in Orthopaedic Surgery: Identifying Potential Barriers to Acceptance and Disparities With Implementation.

INTRODUCTION: Despite growing enthusiasm for artificial intelligence (AI) implementation in orthopaedic care, patient attitudes toward AI adoption rem...

Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases.

OBJECTIVE: To construct and interpret a machine learning model for predicting overall survival in nonsurgical prostate cancer with bone metastases (PC...

Joint effects of physical activity and diet quality on depressive symptoms and all-cause mortality in adults with diabetes: NHANES 2007-2018.

Depressive symptoms are common among adults with diabetes and are associated with adverse clinical outcomes, including mortality. Evidence from genera...