Orthopedics

M44TMD: A multimodal, multi-task deep learning framework for comprehensive assessment of TMD-related abnormalities.

OBJECTIVE: Existing deep learning (DL) approaches for assessing temporomandibular disorders (TMD) are limited by underutilization of magnetic resonance imaging (MRI) in some tasks, a narrow focus on single-task detection, and predominant reliance on unimodal data. This study proposes a multimodal DL framework to address these issues. METHODS: We collected 12,690 MRI slices and clinical data from 7...

Closed Loop Computer-based Artificial Intelligence Model "Maverik" to Help Diagnose and Differential Diagnoses of Childhood Onset Chronic Nonbacterial Osteomyelitis: Pilot Study.

BACKGROUND: Childhood-onset chronic nonbacterial osteomyelitis (CNO) is an inflammatory bone disease that has become better defined in the last 2 decades and is frequently encountered in pediatric rheumatology. As the disease is still not well known and is often confused with malignancy and growth pains, it can easily be missed in clinical practice. We aimed to develop and evaluate a computer-aide...

Machine Learning Photodynamics Unveils a Controlled H2 Loss Channel in the Methaniminium Cation.

The methaniminium cation, CH2NH2+, plays an important role in Titan's N2-CH4 atmospheric chemistry. As the simplest protonated Schiff base (PSB), it a...

Machine Learning-Based Prediction Model for Alveolar Bone Defect Risk Following Orthodontic Treatment.

OBJECTIVES: Alveolar bone defects, such as fenestration and dehiscence, induced by orthodontic treatment represent significant complications that can ...

Recent Advances in Musculoskeletal Radiology: Bridging Innovation and Clinical Application.

Recent advances in musculoskeletal (MSK) radiology have markedly improved diagnostic accuracy through innovations in MRI, CT, and artificial intellige...

Artificial intelligence-assisted detection of soft tissue calcifications and ossifications in CBCT.

OBJECTIVES: This study aimed to integrate soft tissue calcifications and ossifications (STCO) detected on cone beam computed tomography (CBCT) into an...

Prediction of independent ambulation at hospital discharge in patients with proximal femoral fractures based on preoperative clinical information: A retrospective study using extreme gradient boosting and SHapley additive explanations.

BACKGROUND: Independent ambulation at hospital discharge is a critical determinant of discharge destination and caregiving burden in older adults with...

Are social robots more interesting than humans? Quantitative assessment of Joint Attention in autistic and typically developing children.

INTRODUCTION: Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction and communication, including joint attention (JA) impa...

SPP1-CD44 signaling contributes to the mechanisms and therapeutic implications in intervertebral disc degeneration.

BACKGROUND: Intervertebral disc degeneration (IVDD) is a major pathological cause of chronic back pain and reduced mobility. Among emerging molecular ...

Ensemble machine learning for early mortality risk stratification in septic orthopedic trauma: an international cohort study.

BACKGROUND: Sepsis represents a life-threatening complication in severe orthopedic trauma, significantly increasing short-term mortality risk. Despite...

An Unsupervised Learning Approach for Multimodal Low Back Pain Stratification.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study proposes a novel stratification framework for individuals with low back pain (LBP). The met...

Deep learning-based micro-CT grayscale analysis for early detection and staging of osteoporosis in rats.

BACKGROUND: Rat models are widely used in preclinical osteoporosis research to study disease mechanisms and evaluate therapies. Current Micro-CT studi...

Identification of alkaline phosphatase as a putative biomarker of anti-NGF treatment-associated arthropathies: Machine learning-assisted analyses of clinical trial data.

OBJECTIVE: Nerve growth factor (NGF) inhibitors have been shown to provide pain relief in patients with osteoarthritis but are associated with adjudic...

Time-resolved prediction of dental implant biomechanics through integration of finite element analysis, osseointegration dynamics, and deep learning.

BACKGROUND: Dental implant longevity depends on the complex interaction between mechanical stability and biological osseointegration. While finite ele...

A multi-branch ConvNeXt-MaxViT fusion transformer model for radiographic knee osteoarthritis severity assessment with Grad-CAM++ explainability.

CONTEXT: Knee Osteoarthritis (KOA) is a progressive degenerative joint disorder and a major cause of disability worldwide. Radiographic grading using ...

Artificial Intelligence-Driven Decision-Making for Knee Joint Manipulation Following Primary Total Knee Arthroplasty.

BACKGROUND: Manipulation under anesthesia (MUA) is a commonly performed procedure to address postoperative stiffness after total knee arthroplasty (TK...

Development and Validation of an Automated Pipeline for the Detection of Monteggia Fracture Dislocations in Pediatric Radiographs.

BACKGROUND: Monteggia fractures are a complex elbow injury that can be missed in up to 50% of pediatric elbow injuries during initial radiographic ass...

Evaluating an Artificial Intelligence software for opportunistic low bone mineral density and osteoporosis screening: a validation study.

Despite the profound prevalence and fracture risk of osteoporosis, access to the gold standard DXA scans remains limited, especially in rural communit...

Sustainable silk fibroin scaffolds for bone repair: assessing their osteogenic potential via AI-enhanced synchrotron imaging workflow.

Effective bone regeneration requires scaffolds capable of guiding and supporting new mineralized matrix formation. In this study, silk fibroin constru...

Predicting skeletal age from HR-pQCT imaging.

INTRODUCTION: High-resolution peripheral quantitative computed tomography (HR-pQCT) provides detailed bone microarchitecture assessments, but the inte...