Orthopedics

AI detection of knee joint effusion from radiographs: Comparative accuracy of two commercial algorithms.

BACKGROUND: Knee joint effusion might indicate injury even without bony changes. Automated detection from radiographs could improve the sensitivity of AI algorithms. PURPOSE: To compare two commercially available AI algorithms, BoneView and RBfracture, in detecting knee joint effusion. MATERIAL AND METHODS: This retrospective study collected 123 lateral knee radiographs. Detection of knee joint ef...

Accuracy of Fluoroscopic Navigation for Predicting Leg Length and Offset in Primary Hip Arthroplasty.

BACKGROUND: Fluoroscopic-assisted computer navigation is widely used to guide intraoperative decisions on leg length (LL) and offset in primary total hip arthroplasty (THA), but its accuracy remains under-evaluated. This study assessed the precision of a fluoroscopy-based navigation system by comparing its intraoperative predictions to validated postoperative measurements. METHODS: We retrospectiv...

MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-care Ultrasound Devices.

OBJECTIVE: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices. ...

Digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers.

PURPOSE: This scoping review examines current evidence supporting multimodal artificial intelligence, continuous monitoring, and digital twin concepts...

A comprehensive review of ultrasonographic imaging in athletic elbow injuries: a compartment-based approach.

Elbow injury rates are markedly higher among collegiate athletes than in the general population; however, this elevated incidence is largely driven by...

Comparison of radiomics-based models for detection of Modic type 1 changes in photon-counting detector CT images of the lumbar spine.

OBJECTIVE: To compare diagnostic performance of four radiomics-based machine learning models for detecting Modic type 1-changes of the lumbar spine in...

[Use of artificial intelligence for next-gen anamnesis and communication in orthopedics & trauma surgery : From chatbots to ambient intelligence].

BACKGROUND: Against the backdrop of increasing patient volumes, rising case complexity, and physicians' limited time, AI-driven systems for anamnesis,...

Transformer-Based Modular Motion Generation Through Shoulder-Arm Decoupling for Upper Limb Rehabilitation.

The shoulder girdle is one of the most complex components of the upper limb, and when coupled with the arm, modeling and prediction become even more c...

Deep learning-enabled monitoring of postoperative fracture healing on serial radiographs: a 150-patient study using an enhanced YOLOv11 framework.

OBJECTIVES: To develop and validate a deep learning framework for classifying postoperative time-points as a proxy task for monitoring longitudinal fr...

Consistency analysis of AI cell recognition results between non anticoagulant and anticoagulant marrow smear after Wright's staining.

The integration of artificial intelligence with bone marrow cytology represents a significant trend in the application of AI image recognition technol...

Machine learning and neural network algorithms for prediction of C5 palsy after posterior surgery for ossification of posterior longitudinal ligament.

PURPOSE: C5 palsy (C5P) is one of the main postoperative complications of ossification of the posterior longitudinal ligament (OPLL). However, an accu...

Opportunities for deep learning techniques to advance the histological analysis of preclinical models of osteoarthritis beyond ordinal rank systems.

Tools for assessing disease progression are needed to identify and confirm new mechanisms driving osteoarthritis (OA) progression and guide therapeuti...

Opportunistic screening for osteoporosis using chest X-rays and deep learning: A systematic review and meta-analysis.

PURPOSE: To evaluate the diagnostic performance of deep learning (DL) algorithms applied to chest radiographs (CXR) for detecting osteoporosis and ass...

Advanced intelligent drug-device combination systems: regulatory landscapes, technological foundations, and clinical translation.

Drug-device combinations (DDCs) have evolved from simple drug-coated implants into sophisticated intelligent platforms capable of real-time sensing, a...

Comparison of marker-based and markerless motion capture systems to assess gait kinematics and kinetics in children with cerebral palsy.

BACKGROUND: Cerebral Palsy (CP) is a leading cause of childhood motor disability and is frequently assessed through clinical gait analysis using marke...

Digital emergency routing: analysis of feasibility, utilization, and equity implications.

BACKGROUND: Digital emergency care applications offer potential to reduce delays, enhance triage, and improve care coordination, yet evidence remains ...

Opportunistic CT Fatty Muscle Fraction for Outcome Prediction in Patients Undergoing Transcatheter Mitral Valve Edge-to-Edge Repair.

BACKGROUND: Frailty is a risk factor for adverse outcomes in patients undergoing mitral valve transcatheter edge-to-edge repair (M-TEER) and is interr...

Machine Learning-Based Prediction Model for Infectious Complications in Trauma and Its Association With In-Hospital Mortality.

BACKGROUND: Infectious complications, such as sepsis or catheter-related infections, are common and serious sequelae after trauma. Despite their clini...

Osteoarthritis and dementia: contrasting disorders driven by mutual pathways of autophagy, mTOR, GLP-1, AMPK, wnt, and WISP1.

INTRODUCTION: Increased global lifespan is paralleled by a rise in non-communicable diseases with osteoarthritis and dementia, including Alzheimer's d...

[Writing with a system-ChatGPT in the scientific practice of orthopedics and trauma surgery].

With the emergence of generative AI models such as ChatGPT, a new phase of scientific work is also beginning in orthopedics and trauma surgery. As a l...