Latest AI and machine learning research in orthopedics for healthcare professionals.
OBJECTIVE: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices. METHODS: We propose MonoUNet, a novel, highly compact segmentation model consisting of (i) an aggressively reduced U-Net backbone, (ii) a trainable monogenic block that extracts multi-scale local phase features from the input, and (iii) a gating mech...
PURPOSE: This scoping review examines current evidence supporting multimodal artificial intelligence, continuous monitoring, and digital twin concepts in spine care. Our primary aims were to (1) characterize the state of digital twin development in spine care, (2) identify key technological and conceptual gaps, and (3) evaluate translational barriers to clinical implementation. METHODS: A scoping ...
Elbow injury rates are markedly higher among collegiate athletes than in the general population; however, this elevated incidence is largely driven by...
OBJECTIVE: To compare diagnostic performance of four radiomics-based machine learning models for detecting Modic type 1-changes of the lumbar spine in...
BACKGROUND: Against the backdrop of increasing patient volumes, rising case complexity, and physicians' limited time, AI-driven systems for anamnesis,...
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...
OBJECTIVES: To develop and validate a deep learning framework for classifying postoperative time-points as a proxy task for monitoring longitudinal fr...
The integration of artificial intelligence with bone marrow cytology represents a significant trend in the application of AI image recognition technol...
PURPOSE: C5 palsy (C5P) is one of the main postoperative complications of ossification of the posterior longitudinal ligament (OPLL). However, an accu...
Tools for assessing disease progression are needed to identify and confirm new mechanisms driving osteoarthritis (OA) progression and guide therapeuti...
PURPOSE: To evaluate the diagnostic performance of deep learning (DL) algorithms applied to chest radiographs (CXR) for detecting osteoporosis and ass...
Drug-device combinations (DDCs) have evolved from simple drug-coated implants into sophisticated intelligent platforms capable of real-time sensing, a...
BACKGROUND: Cerebral Palsy (CP) is a leading cause of childhood motor disability and is frequently assessed through clinical gait analysis using marke...
BACKGROUND: Digital emergency care applications offer potential to reduce delays, enhance triage, and improve care coordination, yet evidence remains ...
BACKGROUND: Frailty is a risk factor for adverse outcomes in patients undergoing mitral valve transcatheter edge-to-edge repair (M-TEER) and is interr...
BACKGROUND: Infectious complications, such as sepsis or catheter-related infections, are common and serious sequelae after trauma. Despite their clini...
INTRODUCTION: Increased global lifespan is paralleled by a rise in non-communicable diseases with osteoarthritis and dementia, including Alzheimer's d...
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...
Microglial polarization plays a key role in the process of chronic neuropathic pain (CNP). This study aims to investigate the molecular mechanism by w...
PURPOSE: Robotic-assisted surgery (RAS) generates vast amounts of video and robotic data, presenting opportunities for machine learning. Video-based m...