Orthopedics

Dual-energy CT-based virtual monoenergetic imaging via unsupervised learning.

Since its development, virtual monoenergetic imaging (VMI) derived from dual-energy computed tomography (DECT) has been shown to be valuable in many clinical applications. However, DECT-based VMI showed increased noise at low keV levels. In this study, we proposed an unsupervised learning method to generate VMI from DECT. This means that we don't require training and labeled (i.e. high-quality VMI...

Automated labeling using tracked ultrasound imaging: Application in tracking vertebrae during spine surgery.

PURPOSE: Recent advancements in machine learning (ML) allow for rapid analysis of complex image data, which supports the use of ultrasound (US)-based solutions in interventional procedures. These solutions often require large, labeled datasets that can be time-consuming to curate and subject to inter- and intra-labeler variability. This work presents a practical method for automated labeling of US...

Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based Risk Calculator with Explainable Artificial Intelligence (XAI).

BACKGROUND: Tuberculosis spondylitis (TS), also known as Pott's disease, is the most common destructive form of musculoskeletal tuberculosis and poses...

Understanding whole-body inter-personal dynamics between two players using neural granger causality as the explainable artificial intelligence.

Understanding the dynamics of complex, whole-body interpersonal coordination behavior in humans is an important subject in behavioral science. However...

Integrated bioinformatics and network pharmacology to identify and validate macrophage polarization related hub genes in the treatment of osteoarthritis with Astragalus membranaceus.

BACKGROUND: Macrophage polarization exacerbates the pathological processes of osteoarthritis (OA). Astragalus membranaceus (AM) can repair chondrocyte...

End-to-end 2D/3D registration from pre-operative MRI to intra-operative fluoroscopy for orthopedic procedures.

PURPOSE: Soft tissue pathologies and bone defects are not easily visible in intra-operative fluoroscopic images; therefore, we develop an end-to-end M...

Advancing Musculoskeletal Care Using AI and Digital Health Applications: A Review of Commercial Solutions.

Artificial intelligence (AI) and digital health (DH) solutions are reshaping musculoskeletal (MSK) care across diagnostics, treatment planning, workfl...

Robotic-Assisted Arthroscopy Promises Enhanced Procedural Efficiency, Visualization, and Control but Must Overcome Barriers to Adoption.

Robotic-assisted surgery is now well-established in spine surgery and total joint arthroplasty, but its application to arthroscopy has only recently e...

Bioethical Considerations of Deploying Artificial Intelligence in Clinical Orthopedic Settings: A Narrative Review.

Artificial intelligence (AI) has emerged in orthopedics with the potential to improve diagnostic accuracy, optimize surgical workflows, and support pe...

Identification and validation of aging related genes in osteoarthritis.

BACKGROUND: Osteoarthritis (OA) is a degenerative disease associated with aging. Although an increasing body of research suggests a close relationship...

Enhancement and Machine Learning-Based Prediction of Tribological Properties of PC/PBT/GNPs Nanocomposites.

Ternary polycarbonate-poly-(butylene terephthalate)/graphene nanoplatelets (PC-PBT/GNP) nanocomposites were fabricated by melt-compounding. The nanofi...

Identifying Predictors of Failed Back Surgery Syndrome Following Lumbar Spine Surgery: A Machine Learning Approach.

STUDY DESIGN: Retrospective cohort study from a tertiary academic medical center.

Mild to moderate COPD, vitamin D deficiency, and longitudinal bone loss: the Multi-ethnic Study of Atherosclerosis.

OBJECTIVE: Despite the established association between chronic obstructive pulmonary disease (COPD) severity and risk of osteoporosis, even after acco...

Large Language Models in Spine Surgery: A Promising Technology.

Large language models (LLMs) offer potential applications across medical specialties; in spine surgery, opportunities exist to enhance patient care, s...

The analgesic mechanism of electroacupuncture at the central level for neuropathic pain: a review of studies based on animal experiments.

This article analyzes the progress of animal experiments on the analgesic mechanism of electroacupuncture (EA) at the central level for neuropathic pa...

Deep learning-based action recognition for analyzing drug-induced bone remodeling mechanisms.

INTRODUCTION: Understanding the mechanisms of drug-induced bone remodeling is critical for optimizing therapeutic interventions and minimizing adverse...

Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatological condition in children, with reported prevalence ranging from 12...

Differentiation of Healthy Ex Vivo Bovine Tissues Using Raman Spectroscopy and Interpretable Machine Learning.

OBJECTIVES: Integrating machine learning with Raman spectroscopy (RS) shows strong potential for intraoperative guidance in orthopedic procedures, but...

Near-Freezing-Temperature Golgi Neuronal Staining for X-ray Imaging of Human Brain.

Achieving detailed neuronal structural information in large-volume brain tissue has been a longstanding challenge in human brain imaging. A key obstac...

Exploring the genetic characteristics of overweight-related osteoarthritis using machine learning.

This investigation employed a synergistic approach integrating bioinformatics and machine learning methodologies to scrutinize overweight-related oste...