Orthopedics

Letter to the Editor Re: "Deep learning models for lumbar spinal stenosis on MRI: model comparison and clinical benchmarking" by Lee et al. (Eur Spine J [2026] 35:548-558. DOI: 10.1007/s00586-025-09443-2).

Development and validation of a vision transformer model for radiographic assessment of pediatric humeroradial joint alignment.

BACKGROUND: Whether the radiographic assessments of pediatric anatomical (A-HRJA) and nonanatomical humeroradial joint alignment (NA-HRJA) among pediatric orthopedic surgeons (POS) relies on clinical experience remains unknown. No vision transformer (ViT) model for automated and accurate radiographic pediatric HRJAs categorization has been developed and validated. This study aims to evaluate the r...

Fast MRI of bones in the knee - An AI-driven reconstruction approach for adiabatic inversion recovery prepared ultra-short echo time sequences.

PURPOSE: Inversion recovery prepared ultra-short echo time (IR-UTE)-based MRI enables radiation-free visualization of osseous tissue. However, achievi...

Sensory-guided human-machine joint learning accelerates the acquisition of motor imagery brain computer interface control.

Brain-computer interfaces (BCIs) offer the potential to restore function and augment human capabilities. However, non-invasive electroencephalography ...

Risk factors for periodontal ligament area reduction in maxillary central incisors following orthodontic treatment: a retrospective analysis using a deep learning-based CBCT-PDL segmentation network.

OBJECTIVE: To analyze the relevant risk factors causing the reduction of periodontal ligament area (PDLA) of the maxillary central incisor by measurin...

Barriers to AI-supported health management among older adults with chronic orthopedic conditions in China: implications for healthcare delivery and access.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in chronic disease management, yet its adoption among older adults with chronic ortho...

Artificial-Intelligence-Driven Electromyography Adaptation for Elderly Assistance at Physiological, Functional, and Behavioral Levels.

Older adults frequently face difficulties in activities of daily living (ADLs) due to age-related declines in strength, coordination, and perception. ...

Data-efficient Neuroradiology MRI Imaging Protocol Prediction Using Open-weights Large Language Models.

PURPOSE: To evaluate the feasibility of a locally deployable large language model (LLM) system for automated MRI protocol selection addressing data pr...

Predicting Patient-Reported Outcome Measures, Satisfaction, Healthcare Utilization, Mortality, and Return to Work After Total Knee Arthroplasty Using Machine Learning: A 14,900-Patient Study.

BACKGROUND: Patient-reported outcome measures and healthcare utilization metrics are increasingly used to evaluate the success of total knee arthropla...

Machine learning-based prognosis and early death prediction in de novo stage IV breast cancer patients with bone metastasis: a SEER database and multicentre retrospective study.

Bone is the most common site of distant metastasis in breast cancer (BC), and the development of bone metastasis (BM) is associated with reduced survi...

Integration of metabolomics and machine learning algorithm for discovery of early diagnostic biomarkers of osteoporosis.

BACKGROUND: Osteoporosis (OP) is a prevalent metabolic bone disorder and a major public health concern characterized by reduced bone mass and bone mic...

Japan's contributions to hip joint preservation and reconstruction: from osteonecrosis and developmental dysplasia to precision arthroplasty.

PURPOSE: To review Japan's major contributions to hip joint preservation and reconstruction, spanning joint-preservingosteotomy, biomaterials innovati...

Artificial intelligence enabled behavior modeling and dual-task performance analysis of cloud-native software with fused multi-source heterogeneous data.

To address the challenges of heterogeneous multi-source data, inadequate collaborative modeling of temporal and topological features, and low efficien...

Forecasting knee arthroplasty surgery with deep learning : an integrated approach using routine clinical data and radiographs.

AIMS: We aimed to develop and validate a practical deep learning model integrating commonly collected clinical data and knee radiographs to predict th...

Tree-based machine learning models recover rule-based flare labels from virtual symptom diaries in pediatric Behçet's disease: an in silico proof-of-concept study.

Behçet's disease (BD) in childhood is characterised by recurrent inflammatory flares that can result in significant morbidity, most notably with ocula...

Artificial intelligence meets pediatric orthopedics: A comparative analysis of ChatGPT-4o, Gemini 2.0, and Claude 3.5 in detecting supracondylar humeral fractures.

BACKGROUND: Supracondylar humeral fractures constitute 10-16% of pediatric skeletal injuries, requiring timely diagnosis to prevent neurovascular comp...

A Radiomics-Driven Model to Distinguish Between Clinically Similar Myxopapillary Ependymomas and Lumbosacral Schwannomas.

BACKGROUND AND OBJECTIVES: Myxopapillary ependymomas (MPE) and intradural lumbosacral schwannomas may be challenging to distinguish based on presentin...

AI-driven multiscale modeling of mechanical and corrosion properties in biodegradable Mg-Lu alloys.

Magnesium-lutetium (Mg-Lu) alloys exhibit significant potential as biodegradable bone implant materials. However, their low alloying content necessita...

Machine-learning-based Fall-prediction Model for Inpatients in Military Hospitals.

This case-control study develops a machine-learning (ML)-based fall-risk-prediction model for military-hospital inpatients, using electronic records (...

The Role of Artificial Intelligence in Addressing Menopausal Mental Health Challenges.

Menopause marks a crucial transition in a woman's life and is often accompanied by physical and psychological changes that can adversely affect mental...