Rheumatology

Profiling of kidney involvement in systemic lupus erythematosus by deep learning using the National Database of Designated Incurable Diseases of Japan.

BACKGROUND: Kidney involvement frequently occurs in systemic lupus erythematosus (SLE), and its clinical manifestations are complicated. We profiled kidney involvement in SLE patients using deep learning based on data from the National Database of Designated Incurable Diseases of Japan.

Advances in materials-based therapeutic strategies against osteoporosis.

Osteoporosis is caused by the disruption in homeostasis between bone formation and bone resorption. Conventional management of osteoporosis involves systematic drug administration and hormonal therapy. These treatment strategies have limited curative efficacy and multiple adverse effects. Biomaterials-based therapeutic strategies have recently emerged as promising alternatives for the treatment of...

Artificial intelligence and high-dimensional technologies in the theragnosis of systemic lupus erythematosus.

Systemic lupus erythematosus is a complex, systemic autoimmune disease characterised by immune dysregulation. Pathogenesis is multifactorial, contribu...

Detecting hand joint ankylosis and subluxation in radiographic images using deep learning: A step in the development of an automatic radiographic scoring system for joint destruction.

We propose a wrist joint subluxation/ankylosis classification model for an automatic radiographic scoring system for X-ray images. In managing rheumat...

Automatic Segmentation and Classification for Antinuclear Antibody Images Based on Deep Learning.

Antinuclear antibodies (ANAs) testing is the main serological diagnosis screening test for autoimmune diseases. ANAs testing is conducted principally ...

Anti-Jamming Strategy for Federated Learning in Internet of Medical Things: A Game Approach.

Federated learning (FL) is a new dawn of artificial intelligence (AI), in which machine learning models are constructed in a distributed manner while ...

Do artificial neural networks love sex? How the combination of artificial neural networks with evolutionary algorithms may help to identify gender influence in rheumatic diseases.

Although medical research has been performed predominantly on men both in preclinical and clinical studies, continuous efforts have been made to overc...

Qualitative and Artificial Intelligence-based Sentiment Analyses of Anti-LGBTI+ Hate Speech on Twitter in Turkey.

The aim of this study was to evaluate hate speech in Turkish LGBTI+-related tweets during a one-month period of artificial intelligence-based sentimen...

Lorcaserin and phentermine exert anti-obesity effects with modulation of the gut microbiota.

Although drugs have been reported to modulate the gut microbiota, the effects of anti-obesity drugs on the gut microbiota remain unclear. Lorcaserin (...

Rapid simultaneous analysis of anti human immunodeficiency virus drugs in pharmaceutical formulation by smart spectrophotometry based on multivariate calibration and least squares support vector machine methods.

In this study, two chemometrics methods, including partial least squares regression (PLS) and least squares support vector machine (LS-SVM) were appli...

Integrated Damage Location Diagnosis of Frame Structure Based on Convolutional Neural Network with Inception Module.

Accurate damage location diagnosis of frame structures is of great significance to the judgment of damage degree and subsequent maintenance of frame s...

Prediction of coronary heart disease in gout patients using machine learning models.

Growing evidence shows that there is an increased risk of cardiovascular diseases among gout patients, especially coronary heart disease (CHD). Screen...

A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images.

Multiple Sclerosis (MS) is an autoimmune disease that causes brain and spinal cord lesions, which magnetic resonance imaging (MRI) can detect and char...

The design of compounds with desirable properties - The anti-HIV case study.

Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artific...

Position estimation using neural networks in semi-monolithic PET detectors.

. The goal of this work is to experimentally compare the 3D spatial and energy resolution of a semi-monolithic detector suitable for total-body positr...

Scratch-AID, a deep learning-based system for automatic detection of mouse scratching behavior with high accuracy.

Mice are the most commonly used model animals for itch research and for development of anti-itch drugs. Most laboratories manually quantify mouse scra...

GPS Spoofing Detection Method for Small UAVs Using 1D Convolution Neural Network.

The navigation of small unmanned aerial vehicles (UAVs), such as quadcopters, significantly relies on the global positioning system (GPS); however, UA...

Frame Structure Fault Diagnosis Based on a High-Precision Convolution Neural Network.

Structural health monitoring and fault diagnosis are important scientific issues in mechanical engineering, civil engineering, and other disciplines. ...

Reliable prediction of cannabinoid receptor 2 ligand by machine learning based on combined fingerprints.

Cannabinoid receptors, as part of the family of the G protein-coupled receptors (GPCRs), are involved in various physiological functions. Its subtype ...

3-Dimensional Immunostaining and Automated Deep-Learning Based Analysis of Nerve Degeneration.

Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease driven by inflammation and demyelination in the brain, spinal cord, and optic n...