Rheumatology

Development of S4A-BSA-Au NPs for enhanced anti-tumor therapy of canine breast cancer.

S4A ((1,2,3)-1,2-propanediol acetal-zeylenone) is one of the derivatives of zeylenone and exhibits s...

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

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 pub...

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) leve...

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 proce...

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 ide...

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...

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 ...

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

Anti-parasitic peptides (APPs) have been regarded as promising therapeutic candidate drugs against p...

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 bot...

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-bo...

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

BACKGROUND: Autoimmune encephalitis (AE) is a noninfectious emergency with severe clinical attacks. ...

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...

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...

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 an...

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 e...

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 o...

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...

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 pe...

Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.

Neurological disorders affect various aspects of life. Finding drugs for the central nervous system ...

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 aggressiv...