Orthopedics

Apoptotic extracellular vesicles act as master regulators of the bone healing niche.

Apoptotic extracellular vesicles (ApoEVs), natural bilayer nanoparticles released during programmed cell death, have emerged as pivotal regulators and promising therapeutic agents for bone regeneration. They function as innate multimodal signaling entities, expertly coordinating the complex cellular interplay between osteogenesis, angiogenesis, innervation, and immunomodulation required for succes...

Developing an artificial intelligence tool for detecting fractures of child abuse: preliminary findings.

OBJECTIVES: Approximately 6.9% of children in the United Kingdom have suffered physical abuse. Fractures are a common sign and must not be overlooked due to high recurrence and mortality rates. We aimed to train and assess the diagnostic accuracy of a deep learning-based artificial intelligence model (BoneView) in detecting inflicted fractures. MATERIALS AND METHODS: This pragmatic retrospective d...

From predictive accuracy to clinical utility: Model interpretability and the missing bone mineral density data.

This letter to the editor commends the study by Liu et al. on their machine learning model for predicting rib fractures but highlights two crucial cha...

Evaluating the accuracy and feasibility of a commercial AI-powered ergonomic assessment system for automotive assembly work.

Accurate ergonomic risk assessment is essential to prevent work-related musculoskeletal disorders. Artificial intelligence (AI) and computer vision of...

Computational models for predicting bone fracture healing: a review of modeling approaches, predictions, and emerging strategies.

BACKGROUND AND OBJECTIVE: The development of computational models for predicting bone fracture healing process holds strong potential to optimize ther...

Artificial intelligence in orthopedics: current applications, challenges, and future directions.

BACKGROUND: Artificial intelligence research in orthopedics has grown rapidly, yet a substantial gap remains between technical development and clinica...

Underperformance of Machine Learning Models Predicting Readmission and Prolonged Length of Stay Following Total Knee Arthroplasty Among Underrepresented Populations: Fairness Analysis and Mitigation Strategies.

BACKGROUND: While machine learning (ML) models demonstrate high predictive accuracy, recent studies reveal that ML models underperform for smaller sub...

Fuzzy-logic-driven predictions of multi-tissue ingrowth for rapid screening of mechanically instructive tissue-engineering scaffolds.

High retear rates in surgical intervention of interfacial/transitional tissues (bone-tendon, bone-ligament) drive a need to design tissue engineering ...

Multimodal model integrating ultrasound and demographic data for the diagnosis of knee osteoarthritis.

Dynamic modulation of social gaze by sex and familiarity in marmoset dyads.

Social communication relies on the ability to perceive and interpret the direction of others' attention, and is commonly conveyed through head orienta...

An Intelligent Interactive Management Platform for Rheumatoid Arthritis Care: Real-World Observational Study.

BACKGROUND: Effective postdischarge management is essential for maintaining disease control and improving long-term outcomes in rheumatoid arthritis (...

Dosimetry Analysis of 177Lu-PSMA-I&T in Patients with Low-Volume Oligometastatic Hormone-Sensitive Prostate Cancer: A Secondary Analysis of the LUNAR Trial.

The phase 2 LUNAR trial randomized (1:1) patients with oligorecurrent hormone-sensitive prostate cancer to neoadjuvant [177Lu]Lu-PSMA-I&T (2 cycles, 6...

Retinal vascular phenotyping for early detection of coronary artery disease: quantitative assessment and diagnostic modelling.

OBJECTIVES: To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the effi...

Cardiac myofibril networks induce shear stress.

Myofibril arrangement is critical to cardiac muscle function in health and disease. Historically, analysis of the impact of myofibril organisation on ...

Automated Detection and Classification of Radiology Report Discrepancies Using NLP: A Tool for Resident Education and Quality Assurance.

PURPOSE: The aim of this study was to develop and evaluate a natural language processing (NLP) system that automatically detects and classifies discre...

Explainable machine learning to predict muscle loss during radiotherapy for oral cavity cancer.

BACKGROUND AND PURPOSE: Muscle loss during adjuvant radiotherapy is associated with poor survival outcomes in patients with oral cavity cancer (OCC). ...

Large language models in artificial intelligence to answer patient questions in spine surgery: an evaluation of current evidence.

INTRODUCTION: Large language models (LLMs) are increasingly being explored in healthcare, particularly for enhancing patient education. In spine surge...

Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging.

The use of artificial intelligence (AI) in pediatric musculoskeletal imaging has undergone significant expansion over the past few years. Until recent...

Comparative performance of LLMs and machine learning in predicting complications after percutaneous kyphoplasty for osteoporotic vertebral compression fractures.

Exploring large language models (LLMs) performance in the specific medical domain can help understand their generalizability in real-world application...

Assistive Control of Knee Exoskeletons for Human Walking on Sandy Terrain.

Human walkers encounter diverse terrains such as sand and solid ground, which result in distinct gait locomotion and energy costs. This study aims to ...