Arthritis

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. 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...

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 therapeutic development. This review focuses on the advantages and feasibility of leveraging deep learning techniques for quantitative analysis of rodent knee histology in preclinical OA models. Previous studies using radiographs and micro-CT have used deep-le...

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...

Multi-cohort proteogenomic analyses reveal genetic effects across the proteome and diseasome.

Understanding the genetic regulation of circulating protein levels can provide new insights into disease mechanisms. Here, we present the largest prot...

Predicting the risk of venous thromboembolism events in older adults with rheumatoid arthritis after initiating targeted disease-modifying antirheumatic drugs: a comparison of the random survival forest and regularized cox regression models.

OBJECTIVES: To develop a random survival forest (RSF) machine learning (ML) model for predicting venous thromboembolism (VTE) risk in rheumatoid arthr...

Robust disease prognosis via diagnostic knowledge preservation: A sequential learning approach.

Accurate disease prognosis is essential for patient care but is often hindered by the scarcity of longitudinal data. This study explores deep learning...

Explainable multimodal knee osteoarthritis diagnosis from X-ray images using anomaly detection with clinical and structural biomarkers.

Knee Osteoarthritis (KOA) is a common degenerative joint disease that impairs mobility and affects patients' quality of life. Although many studies ha...

Artificial intelligence predictions of knee kinematics, kinetics, and internal biomechanics during walking in people with knee osteoarthritis: A systematic review and meta-analysis.

This review synthesizes current literature on the use of artificial intelligence (AI) to predict knee biomechanics during walking in people with knee ...

Interpretable LightGBM model for predicting postoperative gastrointestinal hemorrhage in elderly hip fracture patients: leveraging systemic inflammation and medication exposures for personalized risk stratification.

BACKGROUND: Postoperative gastrointestinal (GI) bleeding is a serious complication after hip fracture surgery in older adults, yet perioperative risk ...

Fiducial Confidence Intervals for Agreement Measures Among Raters Under a Generalized Linear Mixed Effects Model.

A generalization of the classical concordance correlation coefficient (CCC) is considered under a three-level design where multiple raters rate every ...

Imaging of Small Cell Lung Cancer: An Updated Overview of Current and Emerging Applications.

Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite rec...

Deep Learning-Based Comparison of Knee Minimum Joint Space Width in Patients with Rheumatoid Arthritis and Osteoarthritis Before Total Knee Arthroplasty.

OBJECTIVE: While osteoarthritis (OA) and rheumatoid arthritis (RA) can necessitate total knee arthroplasty (TKA), the mechanisms and radiographic patt...

SIRT1 Downregulation by Advanced Glycation End Products Activates RANKL-Dependent Osteoclast Signaling and Drives Chondrocyte Senescence During Osteoarthritis Development.

Advanced glycation end products (AGEs) accumulate with aging and metabolic stress and are increasingly implicated in osteoarthritis (OA) pathology. Ho...

Advancing IBD Management: A Literature Review on the Role of Non-Invasive Blood-Based Biomarkers in Predicting and Assessing Pharmacodynamic Response to Treatment.

Reliable biomarkers that enable noninvasive, longitudinal assessment of disease activity and therapeutic response remain a major unmet need in inflamm...

Current and Emerging Therapies Targeting the IL-23/IL-17 Axis in Psoriasis.

Over the past two decades, experimental and clinical evidence has established the interleukin-23 (IL-23)/interleukin-17 (IL-17) axis as a key mediator...

Unsupervised Machine Learning Drives Dynamic Alignment Classification In Navigated Total Knee Arthroplasty.

BACKGROUND: Current classifications used for total knee arthroplasty (TKA) are static and fail to capture the dynamic behavior of the limb during gait...

AI-based knee osteoarthritis progression prediction: a comprehensive global bibliometric and hotspot evolution analysis (2010-2025).

BACKGROUND: Knee osteoarthritis (OA) is a leading global cause of disability, yet conventional tools lack sensitivity for early detection and precise ...

Neural Stem Cell-Derived Extracellular Vesicles: The Next Frontier in Neurological and Neurodegenerative Diseases.

The present manuscript provides a comprehensive overview of neural stem cell (NSC)-derived extracellular vesicles (NSC-EVs( as a cell-free approach to...

The complexity of pain in osteoarthritis.

Chronic pain is the hall-mark symptom of osteoarthritis (OA) and although several therapies are available, a sizeable number of patients do not gain a...

Design of Safe and Efficient Adenine Base Editors via Protein Language Model Screening for Osteoarthritis Treatment.

Base editors enable precise genome modification and have emerged as a promising therapeutic approach for correcting diseases caused by single-nucleoti...