Orthopedics

Multimodal deep learning with a joint uncertainty quantification scheme for drug-target interaction prediction.

AI-driven prediction of drug-target interaction (DTI) has emerged as a critical component in modern drug discovery and development. However, this approach is constrained by model and data uncertainties, which substantially affect its reliability and accuracy in DTI prediction. To overcome these limitations, we introduce EUQTri-DTI, a novel evidence-guided uncertainty quantification-based multimoda...

AI-driven Assessment of Vertebral Rotation in Adolescent Idiopathic Scoliosis Using Weight-bearing Cone-beam CT.

RATIONALE AND OBJECTIVES: To evaluate an artificial intelligence (AI)-based algorithm for quantifying vertebral rotation angles on weight-bearing cone-beam CT images in adolescent idiopathic scoliosis (AIS) patients, and to investigate how well the 2D Nash & Moe grading system represents 3D vertebral rotation under weight-bearing conditions. MATERIALS AND METHODS: This prospective study included 7...

Hierarchical classification of acute and chronic osteoporotic vertebral compression fractures of the lumbar spine using X-ray images.

OBJECTIVE: To develop and validate a hierarchical deep learning model for differentiating acute and chronic lumbar osteoporotic vertebral compression ...

A scoping review on the application of new technology in the screening and diagnosis of adolescent idiopathic scoliosis.

INTRODUCTION: Adolescent Idiopathic Scoliosis (AIS) affects 2-4% of adolescents globally. Current screening methods face challenges, including high fa...

A modular soft gripper with enhanced in-hand manipulation capabilities.

Soft robotic grippers offer exceptional adaptability and safety for grasping diverse objects. However, achieving dexterous in-hand manipulation remain...

Diagnostic decision-making, vertebral augmentation, and osteoporosis therapy in vertebral compression fractures: a narrative review.

Vertebral compression fractures (VCFs) represent the most prevalent osteoporotic fracture and constitute a growing cause of morbidity, mortality, and ...

Diagnostic performance and short-interval reproducibility of multimodal large language models in differentiating cholesteatoma from chronic otitis media using key-image temporal bone high-resolution computed tomography.

PURPOSE: This study aimed to assess whether multimodal large language models (LLMs) can distinguish cholesteatoma from non-cholesteatomatous chronic o...

A preliminary analysis of relationship between dual-task gait and age-related cognitive ability using neural network models.

BackgroundAging causes declines in cognitive and motor functions, often manifested in altered gait. Dual-task gait is a sensitive marker for early fun...

Artificial intelligence in lumbar radiography: bridging deep learning and clinical practice in low-resource environments.

BACKGROUND: Artificial intelligence (AI) has increasingly been applied to medical imaging, yet its role in lumbar spine radiography, particularly in l...

Ultra-low dose chest-abdomen-pelvis CT with deep-learning image reconstruction for cancer follow-up: Impact on image quality and lesion detection.

PURPOSE: The purpose of this study was to compare the image quality and lesion detection between ultra-low dose (ULD) chest-abdomen-pelvis computed to...

A Novel Machine Learning-Based Semi-Automated Phantom-Less QCT Model for Osteoporosis Screening on 100 kVp Ultra-Low-Dose Chest CT: A Phantom Study.

RATIONALE AND OBJECTIVES: Opportunistic osteoporosis screening using chest CT is increasingly explored, yet conventional QCT models are calibrated at ...

Fully Automated Segmentation of Anatomical Subregions of the Thoracolumbar Spine on Computed Tomography.

Segmentations of the vertebral column that include anatomical subregions can be used for patient education, pedicle screw planning, or radiomic featur...

Prompt Configurations for Multimodal Large Language Models in Diagnosing and Staging Osteonecrosis of the Femoral Head: Multimodel Retrospective Observational Diagnostic Study.

BACKGROUND: Multimodal large language models (MLLMs) have emerging potential for interpreting medical images and text, but their performance in orthop...

Can ChatGPT pass the polish national medical specialization examination in orthopedics and traumatology?

INTRODUCTION: Artificial intelligence (AI) has evolved rapidly in recent years and is becoming increasingly integrated into many areas of medicine. In...

A Comparison of Machine Learning and Human Graders for Glaucoma Diagnosis from Fundus Images for Population Screening.

PURPOSE: To compare the accuracy of vertical cup-disc ratios (VCDR), ascertained by machine learning (ML) versus human graders, from fundus images for...

KA-TMoE: A Deep Learning Method Using Time-Series CT Radiomics to Predict Post-Radiotherapy Rib Fractures in NSCLC Patients.

BACKGROUND AND PURPOSE: Rib fracture is a recognized clinical complication in medically inoperable patients with non-small cell lung cancer (NSCLC) un...

Distinct recovery phenotypes after hip arthroscopy reveal dissociation between daily function and sports performance.

BACKGROUND: Hip arthroscopy outcomes for femoroacetabular impingement remain heterogeneous. The Hip Outcome Score (HOS) comprises 2 distinct subscales...

Bone age estimation from chest radiographs using deep neural networks: a proof-of-concept study.

BACKGROUND: Bone age (BA) is the gold standard for skeletal maturity assessment but is not routinely incorporated into pediatric growth evaluation wor...

Brain morphometric alterations associated with degenerative scoliosis: a structural MRI study.

STUDY DESIGN: Cross-sectional Study. BACKGROUND: Degenerative scoliosis (DS) is conventionally viewed as a localized spinal biomechanical failure. How...

A β-TCP/PMMA composite bone cement promotes osteogenic differentiation of osteoporotic rBMSCs via Wnt/β-catenin pathway.

Osteoporosis-induced bone defects represent a severe clinical challenge that requires high-performance bone repair biomaterials. To address the limite...