Orthopedics

Predicting Heterogeneity of Treatment Effects to Transcranial Direct Current Stimulation for Knee Osteoarthritis Pain and Symptoms: A Machine Learning Approach.

OBJECTIVES: We identified key predictors of the heterogeneity of treatment effects of transcranial direct current stimulation (tDCS) in individuals with knee osteoarthritis (KOA). METHODS: This is a secondary analysis of a randomized clinical trial involving 60 participants who underwent 15 daily sessions of 2-mA tDCS over three weeks. We applied group-based trajectory modeling to classify partici...

Predicting Treatment Outcomes in Patients With Psoriatic Arthritis or Axial Spondyloarthritis: An Artificial Intelligence-Driven Approach.

OBJECTIVE: To develop machine learning (ML) models to predict the probability at baseline of achieving low disease activity (LDA) and high health-related quality of life (HRQOL) in patients with psoriatic arthritis (PsA) or axial spondyloarthritis (axSpA) treated with secukinumab (SEC). METHODS: AQUILA is an ongoing multicenter, prospective, noninterventional study assessing the effectiveness and ...

3D CSFA-UNet: a unified attention-driven deep learning framework for accurate knee MRI segmentation and osteoarthritis severity classification.

Although several recent multi-task deep learning methods already perform segmentation and classification jointly, many still face limitations in clini...

Evaluation of a markerless motion capture to measure 3D joint kinematics during occupational lifting tasks using mobile devices.

Recent advances in human pose estimation (HPE) have enabled markerless motion capture (MoCap) techniques as a promising alternative to traditional mar...

The Second Skin: A Wearable Sensor Suite That Enables Real-Time Human Biomechanics Tracking Through Deep Learning.

OBJECTIVE: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedbac...

M3C: Resist Agnostic Attacks by Mitigating Consistent Class Confusion Prior.

Adversarial attack is a major obstacle to the deployment of deep neural networks (DNNs) for security-sensitive applications. To address these adversar...

The Challenges With Artificial Intelligence in Scientific Writing.

Artificial intelligence (AI) is rapidly reshaping scientific writing, peer review, and academic publishing. While these technologies offer benefits, i...

Integrative LC-MS/MS, Bioinformatics, and Molecular Dynamics Reveal Multitarget Antioxidant Mechanisms of Bushen Huoxue Decoction in Intervertebral Disc Degeneration.

Intervertebral disc degeneration (IVDD) is a major cause of low back pain and disability. Excessive reactive oxygen species (ROS) disrupt disc homeost...

Automated landmark detection and view positioning assessment of shoulder grashey view radiographs using cascade deep learning: A dual-center validation study.

BACKGROUND: Shoulder Grashey view radiographs are fundamental diagnostic tools in orthopedic practice, with the critical shoulder angle serving as a k...

Identification of Reproducible CT-Image Based Radiomic Features That Predict Shoulder Arthroplasty Outcomes.

The goal of this radiomic analysis is to quantify the sensitivity of radiomic features on computed tomography (CT) image pre-processing parameters and...

Machine Learning Based Prediction of Tibial Insert Thickness in Total Knee Arthroplasty From Intraoperative Knee Joint Laxity Data.

Total knee arthroplasty (TKA) represents the gold standard for relieving pain and restoring function in patients with end-stage knee osteoarthritis. S...

Radiation-free Cobb angle estimation in adolescent scoliosis using surface topography and a linear regression model.

Scoliosis, the most common spinal deformity in adolescents, requires frequent radiographic follow-up, exposing patients to cumulative ionizing radiati...

Event-triggered decentralized adaptive critic learning control for interconnected systems with nonlinear inequality state constraints.

In this paper, an event-triggered decentralized adaptive critic learning (ACL) control method is proposed for interconnected systems with nonlinear in...

Predicting gait kinetics using 3-degrees of freedom acceleration data and artificial neural networks.

BACKGROUND: Motion analysis plays an important role in clinical decision-making and biomechanical research. Conventional assessments rely on laborator...

Disulfidptosis in osteoarthritis: Role of SLC2A3 downregulation and potential therapeutic implications.

OBJECTIVE: Disulfidptosis is a newly recognized form of regulated cell death characterized by actin cytoskeleton collapse under disulfide stress. Rece...

Machine learning for predicting outcomes, complications and resource utilisation after hip arthroscopy: A systematic review.

PURPOSE: Machine learning (ML) algorithms are increasingly used to predict outcomes in orthopaedic surgery, but their utility in hip arthroscopy remai...

Multiclass classification of infections after cervical spine surgery in the elderly: a machine learning approach based on preoperative and perioperative data.

GDPooled transformer: glaucoma detection using pooled attention based transformer with attention mechanism.

Glaucoma is a common eye disease affecting several people worldwide. Blindness can be avoided with proper treatment and regular examination. Delayed d...

Diagnostic accuracy of artificial intelligence models for temporomandibular joint anomalies on MRI: a systematic review and meta-analysis.

BACKGROUND: Artificial intelligence (AI) techniques are increasingly applied to magnetic resonance imaging (MRI) for detecting temporomandibular joint...

Evaluating ChatGPT-5.0 in developmental dysplasia of the hip: A scenario-based validation study against AAOS and AAP guidelines.

PURPOSE: Developmental dysplasia of the hip (DDH) requires timely, guideline-concordant decisions to prevent long-term morbidity. ChatGPT-5.0 may supp...