Rheumatology

Public Perception and Reception of Robotic Applications in Public Health Emergencies Based on a Questionnaire Survey Conducted during COVID-19.

Various intelligent technologies have been applied during COVID-19, which has become a worldwide public health emergency and brought significant challenges to the medical systems around the world. Notably, the application of robots has played a role in hospitals, quarantine facilities and public spaces and has attracted much attention from the media and the public. This study is based on a questio...

Lipoprotein-associated phospholipase A2 and carotid intima-media thickness in primary Sjögren syndrome.

OBJECTIVES: This study aims to evaluate serum lipoprotein-associated phospholipase A2 (Lp-PLA2) level and carotid intima-media thickness in primary Sjögren syndrome (pSS) as an indicator of atherosclerosis.

Job characteristics of a Malaysian bank's anti-money laundering system and its employees' job satisfaction.

Banks and financial institutions are vulnerable to money laundering (ML) as a result of crime proceeds infiltrating banks in the form of significant ...

Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy.

Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and identifying these patients is difficult due to a lack...

Anti-cancer Peptide Recognition Based on Grouped Sequence and Spatial Dimension Integrated Networks.

The diversification of the characteristic sequences of anti-cancer peptides has imposed difficulties on research. To effectively predict new anti-canc...

Anti- in vitro effect of -cyclohexyl-1,2,4-oxadiazole and its ADME/TOX parameters.

Leishmaniasis is a disease that represents a serious global health problem with a potentially fatal outcome in some cases. spp. is transmitted by the...

PredAPP: Predicting Anti-Parasitic Peptides with Undersampling and Ensemble Approaches.

Anti-parasitic peptides (APPs) have been regarded as promising therapeutic candidate drugs against parasitic diseases. Due to the fact that the experi...

An Automatic Knee Osteoarthritis Diagnosis Method Based on Deep Learning: Data from the Osteoarthritis Initiative.

Osteoarthritis (OA) is the most common form of arthritis. According to the evidence presented on both sides of the knee bones, radiologists assess the...

Multiclass classification of whole-body scintigraphic images using a self-defined convolutional neural network with attention modules.

PURPOSE: A self-defined convolutional neural network is developed to automatically classify whole-body scintigraphic images of concern (i.e., the norm...

Deep Learning-Enabled Identification of Autoimmune Encephalitis on 3D Multi-Sequence MRI.

BACKGROUND: Autoimmune encephalitis (AE) is a noninfectious emergency with severe clinical attacks. It is difficult for the earlier diagnosis of acute...

A Novel Anti-Noise Fault Diagnosis Approach for Rolling Bearings Based on Convolutional Neural Network Fusing Frequency Domain Feature Matching Algorithm.

The development of deep learning provides a new research method for fault diagnosis. However, in the industrial field, the labeled samples are insuffi...

Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach.

Alopecia areata is defined as an autoimmune disorder that results in hair loss. The latest worldwide statistics have exhibited that alopecia areata ha...

Machine Learning Approaches in Study of Multiple Sclerosis Disease Through Magnetic Resonance Images.

Multiple sclerosis (MS) is one of the most common autoimmune diseases which is commonly diagnosed and monitored using magnetic resonance imaging (MRI)...

The Role of Deep Learning-Based Echocardiography in the Diagnosis and Evaluation of the Effects of Routine Anti-Heart-Failure Western Medicines in Elderly Patients with Acute Left Heart Failure.

OBJECTIVE: The role of deep learning-based echocardiography in the diagnosis and evaluation of the effects of routine anti-heart-failure Western medic...

Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy.

BACKGROUND: In anti-vascular endothelial growth factor (anti-VEGF) therapy, an accurate estimation of multi-class retinal fluid (MRF) is required for ...

Design, synthesis and mechanistic study of new benzenesulfonamide derivatives as anticancer and antimicrobial agents carbonic anhydrase IX inhibition.

Changes in gene expression cause uncontrolled cell proliferation and consequently tumor hypoxia. The tumor cells shift their metabolism to anaerobic g...

A computational model of familiarity detection for natural pictures, abstract images, and random patterns: Combination of deep learning and anti-Hebbian training.

We present a neural network model for familiarity recognition of different types of images in the perirhinal cortex (the FaRe model). The model is des...

Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade.

Anti-PD-1 immunotherapy has recently shown tremendous success for the treatment of several aggressive cancers. However, variability and unpredictabili...

Future minds and a new challenge to anti-natalism.

Some futurists and philosophers have urged that recent developments in biotechnology promise advancements that challenge standard accepted views of hu...

Discovery of quinolone derivatives as antimycobacterial agents.

Tuberculosis (TB), an infectious disease caused by (), is an important public health issue. Current first-line drugs administered to TB patients have...