Orthopedics

Accurate automated 3D lumbar spine reconstruction from biplanar X-rays using multi-task deep learning and anatomy-aware optimization.

BACKGROUND: Accurate 3D assessment of the weight-bearing lumbar spine is crucial for diagnosing various spinal pathologies. However, existing biplanar X-ray reconstruction methods struggle with complex pathologies and low-contrast structures. PURPOSE: This study aims to propose a fully automated framework for high-accuracy 3D lumbar spine reconstruction from biplanar X-ray images. METHODS: Statist...

Scanner-agnostic artificial intelligence approach for fast bone scintigraphy.

PURPOSE: Current bone scintigraphy protocols often demand full-count, 10-15 min scans to preserve image quality, and existing deep-learning (DL) denoisers typically need to be retrained or retuned for each camera manufacturer. We introduce a scanner-agnostic adaptive-diffusion U-Net designed to reconstruct diagnostic-grade images from half-time or half-dose acquisitions without scanner-specific re...

A stacking based deep learning framework integrating random search neural architecture search for meniscus tear diagnosis.

BACKGROUND: Accurate and rapid diagnosis of meniscal tears is crucial for effective management of sports-related injuries and degenerative knee disord...

Artificial intelligence in knee osteotomy: evolution of alignment assessment and surgical decision-making.

Knee osteotomy remains a fundamental joint-preserving intervention for unicompartmental osteoarthritis and lower limb malalignment, yet traditional tw...

The role of catastrophizing in anxiety and depression symptom scores among knee osteoarthritis patients: a multimodal assessment with EEG and machine learning.

To examine dimensional associations between anxiety- and depression-related symptom severity, pain catastrophizing, and resting-state EEG features in ...

Development and Validation of a Multi-Modal Ensemble Model for Predicting Progression in Idiopathic Scoliosis.

Study DesignRetrospective Cohort Study.ObjectivesAccurate prediction of curve progression in idiopathic scoliosis at the initial visit would facilitat...

Accuracy of Machine Learning Algorithms Based on Electroencephalogram in Sleep Apnea Detection: Systematic Review and Meta-Analysis.

BACKGROUND: Sleep apnea (SA) is a serious sleep disorder, and its diagnostic gold standard, polysomnography, is costly and time-consuming. Electroence...

Infrared Spectroscopy for Determining Bone Graft Healing and Readiness in Tissue Models.

OBJECTIVE: Successful dental implant placement relies on the proper integration of bone graft material into an area of deficient native bone. Traditio...

Incomplete Reporting Persists in Orthopedic Machine Learning Models: A Systematic Review of TRIPOD and TRIPOD+AI Reporting Completeness.

BACKGROUND AND OBJECTIVE: Machine learning (ML) prognostic models in orthopedic surgery are published at an accelerating pace, yet whether reporting m...

Evaluating Training Effectiveness for a Technology-Driven Pain Assessment Application: A Cross-Sectional Study.

PURPOSE: Appropriate pain assessment of adults is critical for effective pain management. Technology-driven tools can contribute to improved pain asse...

Engineering autoimmune disease models using organoids: Harnessing microenvironmental engineering for precision medicine and immunological recapitulation.

Autoimmune diseases-including systemic sclerosis (SSc), systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA)-are increasingly understood ...

Development of a deep learning-based model for personal identification using postmortem CT and antemortem chest x-rays.

PURPOSE: To facilitate personal identification for mass disaster victims, we aimed to develop and evaluate a deep learning method for matching postmor...

Large language models as sources of patient information on robotic knee arthroplasty: a comparative evaluation.

BACKGROUND: Robotic-assisted total knee arthroplasty (rTKA) is increasingly used because of its surgical precision. However, inconsistent outcomes and...

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting...

Stress Reactions in Bone and Stress Fractures.

The term "stress fracture" encompasses a spectrum of bone injuries resulting from repetitive submaximal loading that exceeds the bone's capacity for r...

Deep Learning for Canine Cardiac Radiography: A Comprehensive Review of Automated Vertebral Heart Score Estimation.

Myxomatous mitral valve disease (MMVD) is the most common acquired cardiac disorder in dogs and represents a large proportion of cases encountered in ...

Effect of pilates exercises plus breastfeeding positioning adjustment on artificial intelligence-assessed craniovertebral angle in breastfeeding women with forward head posture: a randomized controlled trial.

Forward head posture (FHP), considered a neuromusculoskeletal disorder, includes those associated with breastfeeding. Pilates is recognized for improv...

Joint action with human versus robot partners across psychological domains: a systematic review.

When they act together, people engage a myriad of cognitive and social processes which are increasingly investigated in various areas of psychological...

Promoting patient empowerment in chronic care: A scoping review of key facilitating factors.

OBJECTIVES: Chronic conditions represent a growing global health challenge, requiring ongoing management in which patients play an active role. Althou...

Clinical justification for osteoporosis investigation: transitioning from opportunistic to diagnostic referrals from alternative forms of imaging.

Clinical justification remains fundamental to the safe use of imaging involving ionising radiation, requiring a favourable balance between diagnostic ...