Orthopedics

Evaluating Conversational Image Segmentation for Medicine: Performance, Failure Modes, and a Fairness Audit Across Seven Modalities

Medical-image segmentation underpins quantitative diagnostics and research, yet state-of-the-art models remain task-specific and data-hungry. The recent emergence of powerful, multimodal large language models (LLMs) presents a generalizable option; however, their efficacy in the specialized medical domain remains largely unquantified. We aim to benchmark the foundational Gemini 2.5 Flash and Gemin...

Artificial Intelligence Predicts Health-Related Quality of Life for Adolescent Idiopathic Scoliosis

Adolescent idiopathic scoliosis (AIS) has a large impact on health-related quality of life (HRQoL) including poor psychosocial functioning, body image, and psychological distress. Surgical management for AIS is common; however, there is limited consensus on preoperative and intraoperative strategies to optimize HRQoL outcomes. Accurate prediction of postoperative outcomes can help guide operative ...

Enhancing Anterior Quadratus Lumborum Block Accuracy with Artificial Intelligence: A Segmentation Approach Evaluated by Dice Score Metrics

Anterior quadratus lumborum (QL) block is a regional anesthesia technique shown to provide both somatic and visceral pain relief by targeting lower th...

Arachnoiditis: Leveraging crowdsourcing and AI in a cross-sectional study of 1,105 cases to improve identification, understanding, and treatment

Arachnoiditis, a painful and potentially disabling neurological condition, results from persistent inflammation of the spinal cord pia-arachnoid membr...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughpu...

Identification and validation of biomarkers FAM107A, RHOBTB1 and ZBTB16 associated with dietary restriction in osteoarthritis

Osteoarthritis (OA), a chronic ailment that leads to joint degeneration, could be prevented by dietary restriction (DR). This study investigated the m...

Prevalence and Predictors of Silent Vertebral Compression Fractures: A Cross-Sectional Population-Based Study Using UK Biobank Imaging Data

To estimate the prevalence of silent vertebral compression fractures (VCF) in an asymptomatic population and to assess the demographic and clinical pr...

Detecting Scoliosis at Scale Using Automated Cobb Angle Analysis in the UK Biobank

Adult degenerative scoliosis arises after skeletal maturity in an initially normal spine, primarily driven by age-related degeneration. The Cobb angle...

Machine learning model predicts new-onset lower extremity deep vein thrombosis after pelvic fracture surgery and targeted diagnosis

Postoperative new-onset deep vein thrombosis (PNO-DVT) of the lower extremities represents a prevalent and serious clinical complication following pel...

autoscoRA: Deep Learning to Automate Sharp/van der Heijde Scoring of Radiographic Damage in Rheumatoid Arthritis

Regular imaging by conventional radiography to assess for joint damage is a cornerstone in the management of rheumatoid arthritis (RA). Scoring system...

A Federated Learning-based Optic Disc and Cup Segmentation Model for Glaucoma Monitoring In Color Fundus Photographs

Glaucoma, a leading cause of blindness worldwide, depends on accurate optic nerve head assessment, particularly optic disc and cup segmentation, for d...

Glaucoma Detection Using Deep Learning and Prompt-Based Explainable Report Generation

Glaucoma is a leading cause of irreversible blindness and requires early detection to prevent vision loss. This study proposes a novel framework for a...

The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization.

BACKGROUND: Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; t...

Prediction of post-Schroth Cobb angle changes in adolescent idiopathic scoliosis patients based on neural networks and surface electromyography.

INTRODUCTION: To develop a temporal-convolutional-LSTM (TCN-LSTM) hybrid model integrating surface electromyography (sEMG) signals for forecasting pos...

MRI-based 2.5D deep learning radiomics nomogram for the differentiation of benign versus malignant vertebral compression fractures.

OBJECTIVE: Vertebral compression fractures (VCFs) represent a prevalent clinical problem, yet distinguishing acute benign variants from malignant path...

Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-based bone remodeling prediction.

BACKGROUND: Childhood obesity poses a significant risk to bone health, but the impact of insulin resistance (IR) on bone metabolism in prepubertal chi...

Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players.

OBJECTIVE: Early detection of knee osteoarthritis is crucial for improving patient outcomes. While conventional imaging methods often fail to detect e...

Self-tuning trajectory tracking control for concrete pouring construction robots based on PID-NFTSMC and CPO algorithm.

This paper presented a self-tuning trajectory tracking control strategy for concrete pouring construction robots operating under external disturbances...

Deep learning approaches for quantitative and qualitative assessment of cervical vertebral maturation staging systems.

To investigate the potential of artificial intelligence (AI) in Cervical Vertebral Maturation (CVM) staging, we developed and compared AI-based qualit...

Exploring the Mechanisms of Sanguinarine in the Treatment of Osteoporosis by Integrating Network Pharmacology Analysis and Deep Learning Technology.

BACKGROUND: Sanguinarine (SAN) has been reported to have antioxidant, antiinflammatory, and antimicrobial activities with potential for the treatment ...