Rheumatology

Latest AI and machine learning research in rheumatology for healthcare professionals.

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Complementary Memtransistor-Based Multilayer Neural Networks for Online Supervised Learning Through (Anti-)Spike-Timing-Dependent Plasticity.

We propose a complete hardware-based architecture of multilayer neural networks (MNNs), including el...

Artificial Intelligence and Deep Learning for Rheumatologists.

Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing fiel...

Modeling and insights into the structural characteristics of drug-induced autoimmune diseases.

The incidence and complexity of drug-induced autoimmune diseases (DIAD) have been on the rise in rec...

De novo design of anti-tuberculosis agents using a structure-based deep learning method.

Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both...

Shared subspace-based radial basis function neural network for identifying ncRNAs subcellular localization.

Non-coding RNAs (ncRNAs) play an important role in revealing the mechanism of human disease for anti...

High-resolution knee plain radiography image synthesis using style generative adversarial network adaptive discriminator augmentation.

In this retrospective study, 10,000 anteroposterior (AP) radiography of the knee from a single insti...

Comparing two machine learning approaches in predicting lupus hospitalization using longitudinal data.

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease characterized by flares ran...

From real-world electronic health record data to real-world results using artificial intelligence.

With the worldwide digitalisation of medical records, electronic health records (EHRs) have become a...

Deep Learning-Based Medical Data Association Rules to Explore the Connectivity and Regulation Mechanism of miRNA-mRNA Network in Myocarditis.

Acute, chronic myocarditis as myocardial localized or diffuse inflammation lesions is usually involv...

HEp-2 image classification using a multi-class and multiple-binary classifier.

In medicine, identifying the indirect immunofluorescence of human epithelial type 2 (HEp-2) cells pl...

A systematic review of robot-assisted anti-reflux surgery to examine reporting standards.

Robot-assisted anti-reflux surgery (RA-ARS) is increasingly being used to treat refractory gastro-oe...

Prediction of the Lotus Effect on Solid Surfaces by Machine Learning.

Superhydrophobic surfaces with the "lotus effect" have wide applications in daily life and industry,...

Development of GBRT Model as a Novel and Robust Mathematical Model to Predict and Optimize the Solubility of Decitabine as an Anti-Cancer Drug.

The efficient production of solid-dosage oral formulations using eco-friendly supercritical solvents...

Recent advances in the use of machine learning and artificial intelligence to improve diagnosis, predict flares, and enrich clinical trials in lupus.

PURPOSE OF REVIEW: Machine learning is a computational tool that is increasingly used for the analys...

Anti-Colorectal Cancer Effects of (Bull.: Fr.) P. Karst. Spore Powder through Regulation of Gut Microbiota-Mediated JAK/STAT Signaling.

(Bull.: Fr.) P. Karst. spore powder (IHS) contains polyphenols and triterpenoids with pharmacologic...

Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence.

Nowadays, supercritical CO(SC-CO) is known as a promising alternative for challengeable organic solv...

The Artificial Intelligence System for the Generation of Sports Education Guidance Model and Physical Fitness Evaluation Under Deep Learning.

In recent years, China's achievements in artificial intelligence (AI) have attracted the attention o...

Simultaneous regression and classification for drug sensitivity prediction using an advanced random forest method.

Machine learning methods trained on cancer cell line panels are intensively studied for the predicti...

Revisiting Light Field Rendering With Deep Anti-Aliasing Neural Network.

The light field (LF) reconstruction is mainly confronted with two challenges, large disparity and th...

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