Latest AI and machine learning research in orthopedics for healthcare professionals.
BACKGROUND: Early diagnosis of knee osteoarthritis (KOA) is often delayed due to reliance on subjective interpretation of radiographs. Recent advances in artificial intelligence (AI)-based automated Kellgren-Lawrence (KL) grading offer the potential to improve diagnostic accuracy and enable earlier nonoperative treatment. However, the cost-effectiveness of such AI tools has not been comprehensivel...
BACKGROUND: Lumbar disc herniation (LDH) is a major cause of low back pain and radicular leg pain. Percutaneous endoscopic lumbar discectomy (PELD) is a widely used minimally invasive procedure for the treatment of LDH; however, recurrent lumbar disc herniation (RLDH) after surgery remains a significant clinical challenge. Recent studies have explored the application of machine learning (ML) model...
OBJECTIVES: To characterize chin morphology and investigate its associations with sex, as well as various sagittal and vertical skeletal patterns. MAT...
BACKGROUND: The study of spinopelvic alignment in asymptomatic individuals is essential for understanding physiological sagittal balance and establish...
BACKGROUND: Osteoporosis is a metabolic bone disease characterized by reduced bone mass and microarchitectural deterioration, with complex involvement...
OBJECTIVES: To evaluate the diagnostic performance of the large language model (LLM) Gemini 2.5 for cholesteatoma detection using histopathology as th...
OBJECTIVES: Although advancements in electronic health records (EHRs) have improved clinical productivity, digital administrative responsibilities hav...
PURPOSE: Posterior spinal fusion (PSF) with pedicle screws is the standard treatment for adolescent idiopathic scoliosis (AIS) with curves > 45°, yet ...
In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites, using t...
Artificial intelligence (AI) has shown promise in detecting and characterizing musculoskeletal diseases from radiographs. However, most existing model...
INTRODUCTION: Artificial intelligence is gaining significant traction, particularly in the orthopedic literature. To date, there has been no published...
BACKGROUND AND OBJECTIVES: Large Language Models (LLMs) are increasingly used by healthcare professionals and patients for medical information synthes...
OBJECTIVES: This study aims to provide a comprehensive bibliometric mapping of the scientific evolution and research trends of fractal analysis (FA) i...
Deep learning and prior-image-guided cross modality motion reconstruction methods have recently en abled faster acquisition time and lower artifacts i...
Brain dynamics are constrained by the underlying topology of neuronal networks. How genes collaborate to organize these neural networks during develop...
OBJECTIVE: This study aimed to evaluate the accuracy of predicting final adult height (FAH) in Korean girls with central precocious puberty (CPP) usin...
This study presents a patient-specific parametric model of the temporomandibular joint, designed to be semi-automated, and reproducible for multiple p...
High mammographic density is a well-known risk factor for breast cancer and reduces the sensitivity of mammography-based screening. While automated ma...
Mechanical complications in dental implantology often arise from a mismatch between standardized geometries and patient-specific anatomical constraint...
The development of deep learning models for 3D knee MRI analysis is critically constrained by the scarcity of large, annotated datasets. Few-shot lear...