Orthopedics

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 deformity (ASD) patients undergoing surgical correction and to identify predictors of achieving the patient-acceptable symptom state (PASS) both preoperatively and at 2-year follow-up. METHODS: This retrospective analysis of a prospective, multicente...

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 immune system by capturing and eliminating pathogens. This exploratory study aimed to preliminarily identify biomarkers associated with NETs in osteoporosis with diabetes and to provide initial insights into underlying molecular mechanisms. A transc...

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...

Illuminating the black box of traditional Chinese medicine: The pivotal role of transgenic fluorescent zebrafish.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) holds significant therapeutic potential, yet its modernization is hindered by the i...

Artificial intelligence in emergency skeletal X-ray: post-deployment monitoring and clinical impact of incorrect AI results.

OBJECTIVES: This study evaluates the impact of the artificial intelligence (AI) application BoneViewTM within a radiographer-supervised clinical workf...

A metabolomics-driven machine learning model for osteoporosis risk prediction.

Osteoporosis, marked by decreased bone mineral density (BMD), poses a major public health concern by increasing fracture risk, lowering quality of lif...

Boundary sensitive-net-based lumbar vertebra segmentation and spondylolisthesis measurement.

Lumbar spine disorders represent a significant public health concern, with accurate diagnosis relying on vertebral segmentation and quantification. Tr...

Zero Echo Time Magnetic Resonance Imaging of the Spine.

Zero echo time magnetic resonance imaging is an ultrashort echo time technique that enables computed tomography-like visualization of cortical and tra...

Letter to the Editor concerning "External validation of SpineNetv2 deep learning system for automated lumbar spine MRI analysis: A multi-pathology diagnostic agreement study" by Wu et al. (Eur spine J [2025]; https://doi.org/10.1007/s00586-025-09543-z).

Experimental investigation of muscle-tendon unit geometry and kinematics in lower-limb muscles during gait: Current applications and future directions - A scoping review.

PURPOSE: Musculoskeletal (MSK) modeling and ultrasound imaging (USI) are complementary techniques that, when combined with three-dimensional gait anal...

Evaluation of ChatGPT-5 responses to patient-centered questions on stromal vascular fraction for knee osteoarthritis: fair to good quality and content.