Orthopedics

A hierarchical multifunctional cross fusion network for emotion recognition from facial expressions and peripheral physiological signals.

Objective.Accurate emotion recognition is essential for enabling adaptive and empathetic human-computer interaction. However, emotion recognition based on a single modality may be affected by modality-specific noise, weak emotional cues, and individual differences. This study aimed to develop a practical non-invasive emotion recognition framework by integrating facial expressions and peripheral ph...

The Basic Science of Large Language Models in Orthopaedic Surgery.

Orthopaedic surgeons routinely consult search engines, journals, and curated websites to stay current on orthopaedic knowledge. The emergence of large language models, such as OpenAI ChatGPT and Google MedGemma, is changing the way we search for information and how residents learn. Although many orthopaedic surgeons are users of artificial intelligence (AI), most are uncertain about how these tool...

Implementation and Evaluation of an AI-Assisted Telerehabilitation System for Postdischarge Continuation of Rehabilitative Care: Protocol for a Randomized Controlled Trial.

BACKGROUND: The World Health Organization (WHO) launched a Rehabilitation 2030 initiative to call for global action to scale up rehabilitation efforts...

Can Artificial Intelligence Assess Distal Radius Fracture Stability?

BACKGROUND: Accurate assessment of distal radius fracture stability is essential for appropriate triage and timely referral to hand specialists. The L...

Three-dimensional and artificial intelligence-assisted preoperative templating in total hip arthroplasty: a systematic review and meta-analysis.

BACKGROUND: Preoperative templating in total hip arthroplasty (THA) optimizes implant sizing and positioning accuracy. Standard practice relies on two...

A Deep Nonlinear Subspace Modeling and Reconstruction for Diffusion-Weighted Imaging Using Denoising Auto-Encoder.

PURPOSE: To present a novel, nonlinear subspace modeling and joint k-q-space reconstruction technique for high-resolution, multi-band, multi-shell dif...

Machine learning assisted prediction of cartilage histology using MR fingerprinting - a preliminary study.

INTRODUCTION: Prediction of cartilage structural properties through MRI could allow earlier detection of joint pathologies, such as osteoarthritis. MA...

Multi-source information fusion using CNN-LSTM-Attention for bone layer recognition in robotic orthopedic grinding.

Epiphyseal opening requires precise localization for bony bridge resection. Traditional surgery is challenged by unclear bony bridge boundary localiza...

Bo-Net: Deep learning-based model for automatic bone stromal cell segmentation of fluorescence microscopy images.

BACKGROUND AND OBJECTIVES: Bone is a multicellular organ that is the site of complex pathophysiological events (such as cancer). 3D confocal and multi...

Explainable Machine Learning for Perioperative Risk Stratification of Radiographic Adjacent Segment Degeneration After Short-Segment Lumbar Fusion.

STUDY DESIGN: Retrospective Cohort Study. OBJECTIVES: To develop and externally validate an explainable machine-learning framework for perioperative r...

Automatic Classification of Anterior Talofibular Ligament Based on 2D Convolutional Neural Network.

OBJECTIVE: To investigate the feasibility of 2D convolutional neural networks (CNNs) in the automatic classification of anterior talofibular ligaments...

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review.

PURPOSE: To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting kn...

Quantitative Temporal Bone Analysis of Stria Vascularis, Spiral Ganglion, and Vestibular Ganglion Cells in Sickle Cell Disease at Young Ages.

OBJECTIVES: Sensorineural hearing loss (SNHL) and vestibular symptoms in sickle cell disease (SCD) may result from hypoxic damage of inner ear structu...

Peripheral blood profiles reflecting progenitor lineage balance are associated with molecular response in chronic myeloid leukemia.

Early achievement of deep remission improves patients' outcome in chronic myeloid leukemia (CML) treatment, highlighting the need for predictive indic...

Predicting time-to-event clinical outcomes with multivariate repeated measurements of patient-level covariates: A systematic review.

OBJECTIVE: Repeated measurements capture the progression of health over time and may inform survival prediction. The goal of this review is to identif...

Deep learning-assisted mapping of dendritic spines using sequential 2D two-photon calcium imaging.

Neurons transform complex spatiotemporal synaptic inputs into structured action potential sequences. Excitatory inputs initiate or interact with dendr...

Investigating the use, role, and accuracy of generative artificial intelligence in anatomical illustration.

This study investigated the potential role of generative artificial intelligence (Gen AI) in creating and enhancing anatomical illustrations. Human ma...

A machine learning-based framework for individualized physical activity and strength targets related to women's bone health.

While substantial evidence supports the associations between physical activity and bone health, the present study aims to advance the field by applyin...

Predictive accuracy of a general-purpose artificial intelligence model for cut-out following proximal femoral nailing.

INTRODUCTION: Cut-out is the most consequential mechanical complication after proximal femoral nailing and requires prompt recognition. General-purpos...

Novel Robotic Control Methods That Account for System Compliance Decrease the Errors in Ligament Tensions Computed Using the Superposition Method.

Superposition testing is a method to quantify in situ ligament tension by measuring the change in joint loads before and after ligament sectioning. De...