Arthritis

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence.

Artificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect and characterize abnormalities as well as monitor disease response. Many AI-based image interpretation tasks for musculoskeletal (MSK) pathologies have...

Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN.

PURPOSE: Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Radiologists usually review knee X-ray images and grade the severity of the impairments according to the Kellgren-Lawrence grading scheme. However, this approach becomes inefficient in hospitals with high throughput as it is time-consuming, tedious and also subjective. This paper introduces a model fo...

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data.

Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and current treatment options are limited to symptomatic relief. P...

Crocin exerts improving effects on indomethacin-induced small intestinal ulcer by antioxidant, anti-inflammatory and anti-apoptotic mechanisms.

Crocin is a plant-derived carotenoid and bears potent antioxidant property. Ranitidine (a histamine H receptor blocker) is used for peptic ulcer treat...

Deep segmentation leverages geometric pose estimation in computer-aided total knee arthroplasty.

Knee arthritis is a common joint disease that usually requires a total knee arthroplasty. There are multiple surgical variables that have a direct imp...

Deep Learning for Lesion Detection, Progression, and Prediction of Musculoskeletal Disease.

Deep learning is one of the most exciting new areas in medical imaging. This review article provides a summary of the current clinical applications of...

Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S.

Cathepsin S (CatS), a member of cysteine cathepsin proteases, has been well studied due to its significant role in many pathological processes, includ...

The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches.

BACKGROUND: The response to treatment for juvenile idiopathic arthritis (JIA) can be staged using clinical features. However, objective laboratory bio...

Mitochondrial dysfunction in rheumatoid arthritis: A comprehensive analysis by integrating gene expression, protein-protein interactions and gene ontology data.

Several studies have reported mitochondrial dysfunction in rheumatoid arthritis (RA). Many nuclear DNA (nDNA) encoded proteins translocate to mitochon...

Machine Learning to Predict Anti-Tumor Necrosis Factor Drug Responses of Rheumatoid Arthritis Patients by Integrating Clinical and Genetic Markers.

OBJECTIVE: Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can provide valuable information on effective drug selecti...

Antibiotic therapy in patients with high prostate-specific antigen: Is it worth considering? A systematic review.

: To address the question of whether antibiotic therapy can obviate the need for prostate biopsy (PBx) in patients presenting with high prostate-speci...

HPLC-MS/MS method for the determination and pharmacokinetic study of six compounds against rheumatoid arthritis in rat plasma after oral administration of the extract of Caulophyllum robustum Maxim.

Caulophyllum robustum Maxim (CRM) is a well-known traditional Chinese medicine (TCM) mainly present in the northeast, northwest and southwest regions ...

Antioxidant, Anti-Melanogenic and Anti-Wrinkle Effects of .

In this study, the antioxidant, anti-xanthine oxidase, anti-melanogenic and anti-wrinkle effects of methanol (ME) and hot water (HE) extracts from the...

Super-resolution reconstruction of knee magnetic resonance imaging based on deep learning.

BACKGROUND AND OBJECTIVE: With the rapid development of medical imaging and intelligent diagnosis, artificial intelligence methods have become a resea...

Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs.

BACKGROUND: Sex and age have long been known to affect the ECG. Several biologic variables and anatomic factors may contribute to sex and age-related ...

Estimation of Vertical Ground Reaction Force Using Low-Cost Insole With Force Plate-Free Learning From Single Leg Stance and Walking.

For the evaluation of pathological gait, a machine learning-based estimation of the vertical ground reaction force (vGRF) using a low-cost insole is p...

Identifying key gait features associated with the radiological grade of knee osteoarthritis.

PURPOSE: Knee osteoarthritis (KOA) is characterized by pain and decreased gait function. This study assessed key features that can be used as mechanic...

Ultrasound-Guided Adductor Canal Block versus Combined Adductor Canal and Infiltration between the Popliteal Artery and the Posterior Capsule of the Knee Block for Osteoarthritis Knee Pain.

CONTEXT: Minimally invasive therapeutic modalities have been used to relieve refractory pain of knee osteoarthritis (OA).

Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis.

This study's objectives were to test correlations among groups of biomarkers that are associated with condylar morphology and to apply artificial inte...

Utility of deep learning super-resolution in the context of osteoarthritis MRI biomarkers.

BACKGROUND: Super-resolution is an emerging method for enhancing MRI resolution; however, its impact on image quality is still unknown.