Arthritis

Deep learning image enhancement for confident diagnosis of TMJ osteoarthritis in zero-TE MR imaging.

OBJECTIVES: This study aimed to evaluate the effectiveness of deep learning method for denoising and artefact reduction (AR) in zero echo time MRI (ZTE-MRI). Also, clinical applicability was evaluated by comparing image diagnosis to the temporomandibular joint (TMJ) cone-beam CT (CBCT).

Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.

Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including diabetes, atherosclerosis, and rheumatoid arthritis. Moreover, histone deacetylases (HDACs), specifically HDAC6 is required for the NLRP3 inflammasome to assemble and activate. Thus, NLRP3 serves as an attractive target for the development of novel ther...

Analytical Quality by Design for Chiral Pharmaceuticals: A Robust HPLC Method for Upadacitinib Enantiomeric Quantification.

Ensuring the enantiomeric purity of chiral pharmaceuticals is paramount for patient safety and therapeutic efficacy. Upadacitinib (UPA), a vital Janus...

CLIP-KOA: Enhancing Knee Osteoarthritis Diagnosis with Multi-Modal Learning and Symmetry-Aware Loss Functions

Knee osteoarthritis (KOA) is a universal chronic musculoskeletal disorders worldwide, making early diagnosis crucial. Currently, the Kellgren and La...

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction

Knee osteoarthritis (KOA) is a common joint disease that causes pain and mobility issues. While MRI-based deep learning models have demonstrated sup...

Applying Machine Learning to Gait Analysis Data for Hip Osteoarthritis Diagnosis.

BACKGROUND: Hip osteoarthritis (OA) is a degenerative joint disease that affects approximately 25% of individuals over their lifetime, with prevalence...

CLOC: Contrastive Learning for Ordinal Classification with Multi-Margin N-pair Loss

In ordinal classification, misclassifying neighboring ranks is common, yet the consequences of these errors are not the same. For example, misclassi...

Putting the Segment Anything Model to the Test with 3D Knee MRI - A Comparison with State-of-the-Art Performance

Menisci are cartilaginous tissue found within the knee that contribute to joint lubrication and weight dispersal. Damage to menisci can lead to onse...

An objective diagnosis of gout and calcium pyrophosphate deposition disease with machine learning of Raman spectra acquired in a point-of-care setting.

OBJECTIVE: Raman spectroscopy is proposed as a next-generation method for the identification of monosodium urate (MSU) and calcium pyrophosphate (CPP)...

[Machine learning models established to distinguish OA and RA based on immune factors in the knee joint fluid].

Objective Based on 25 indicators including immune factors, cell count classification, and smear results of the knee joint fluid, machine learning mode...

Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis.

BACKGROUND: Individuals with hyperuricemia (HUA) are widely recognized as being at increased risk for gout. This study aimed to investigate how physic...

A Multi-Site Study on AI-Driven Pathology Detection and Osteoarthritis Grading from Knee X-Ray

Introduction: Bone health disorders like osteoarthritis and osteoporosis pose major global health challenges, often leading to delayed diagnoses due...

Regulation of Dendritic Cell Function by Ermiaosan via the EP4-cAMP-CREB Signaling Pathway

Ermiao San (EMS), a traditional Chinese medicine composed of Atractylodes macrocephala and Cortex Phellodendron, has demonstrated therapeutic effica...

BioX-CPath: Biologically-driven Explainable Diagnostics for Multistain IHC Computational Pathology

The development of biologically interpretable and explainable models remains a key challenge in computational pathology, particularly for multistain...

Assessing the effects of immune checkpoint inhibitors on bone utilizing machine learning-assisted opportunistic quantitative computed tomography.

Immune checkpoint inhibitors (ICIs) are widely used in cancer treatment, yet their impact on bone health remains unclear. This study aimed to perform ...

Mono2D: A Trainable Monogenic Layer for Robust Knee Cartilage Segmentation on Out-of-Distribution 2D Ultrasound Data

Automated knee cartilage segmentation using point-of-care ultrasound devices and deep-learning networks has the potential to enhance the management ...

Detecting Heel Strike and toe off Events Using Kinematic Methods and LSTM Models

Accurate gait event detection is crucial for gait analysis, rehabilitation, and assistive technology, particularly in exoskeleton control, where pre...

Deep learning enables automatic detection of joint damage progression in rheumatoid arthritis-model development and external validation.

OBJECTIVES: Although deep learning has demonstrated substantial potential in automatic quantification of joint damage in RA, evidence for detecting lo...

SAMRI-2: A Memory-based Model for Cartilage and Meniscus Segmentation in 3D MRIs of the Knee Joint

Accurate morphometric assessment of cartilage-such as thickness/volume-via MRI is essential for monitoring knee osteoarthritis. Segmenting cartilage...

Representation Learning to Advance Multi-institutional Studies with Electronic Health Record Data

The adoption of EHRs has expanded opportunities to leverage data-driven algorithms in clinical care and research. A major bottleneck in effectively ...