Lupus

Deep Reinforcement Learning for personalized diagnostic decision pathways using Electronic Health Records: A comparative study on anemia and Systemic Lupus Erythematosus.

BACKGROUND: Clinical diagnoses are typically made by following a series of steps recommended by guidelines that are authored by colleges of experts. Accordingly, guidelines play a crucial role in rationalizing clinical decisions. However, they suffer from limitations, as they are designed to cover the majority of the population and often fail to account for patients with uncommon conditions. Moreo...

DeepAIP: Deep learning for anti-inflammatory peptide prediction using pre-trained protein language model features based on contextual self-attention network.

Non-steroidal anti-inflammatory drugs (NSAIDs), glucocorticoids, and other immunosuppressants are commonly used medications for treating inflammation. However, these drugs often come with numerous side effects. Therefore, finding more effective methods for inflammation treatment has become more necessary. The study of anti-inflammatory peptides can effectively address these issues. In this work, w...

PepNet: an interpretable neural network for anti-inflammatory and antimicrobial peptides prediction using a pre-trained protein language model.

Identifying anti-inflammatory peptides (AIPs) and antimicrobial peptides (AMPs) is crucial for the discovery of innovative and effective peptide-based...

Approved drugs successfully repurposed against based on machine learning predictions.

Drug repurposing is a promising approach towards the discovery of novel treatments against Neglected Tropical Diseases, such as Leishmaniases, present...

Squid-Inspired Anti-Salt Skin-Like Elastomers With Superhigh Damage Resistance for Aquatic Soft Robots.

Cephalopod skins evolve multiple functions in response to environmental adaptation, encompassing nonlinear mechanoreponse, damage tolerance property, ...

GNN-DDAS: Drug discovery for identifying anti-schistosome small molecules based on graph neural network.

Schistosomiasis is a tropical disease that poses a significant risk to hundreds of millions of people, yet often goes unnoticed. While praziquantel, a...

Deep reinforcement learning control of combined chemotherapy and anti-angiogenic drug delivery for cancerous tumor treatment.

By virtue of the chronic and dangerous nature of cancer, researchers have explored various approaches to managing the abnormal cell growth associated ...

Applying 12 machine learning algorithms and Non-negative Matrix Factorization for robust prediction of lupus nephritis.

Lupus nephritis (LN) is a challenging condition with limited diagnostic and treatment options. In this study, we applied 12 distinct machine learning ...

Machine learning-based integration develops a multiple programmed cell death signature for predicting the clinical outcome and drug sensitivity in colorectal cancer.

Tumorigenesis and treatment are closely associated with various programmed cell death (PCD) patterns. However, the coregulatory role of multiple PCD p...

A deep learning model for anti-inflammatory peptides identification based on deep variational autoencoder and contrastive learning.

As a class of biologically active molecules with significant immunomodulatory and anti-inflammatory effects, anti-inflammatory peptides have important...

Artificial intelligence applications for immunology laboratory: image analysis and classification study of IIF photos.

Artificial intelligence (AI) is increasingly being used in medicine to enhance the speed and accuracy of disease diagnosis and treatment. AI-based ima...

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic s...

Investigation of ferroptosis-associated molecular subtypes and immunological characteristics in lupus nephritis based on artificial neural network learning.

BACKGROUND: Lupus nephritis (LN) is a severe complication of systemic lupus erythematosus (SLE) with poor treatment outcomes. The role and underlying ...

Evaluation of Serum Visfatin as a Biomarker of Lupus Nephritis in Egyptian Patients with Systemic Lupus Erythematosus.

One of the most significant consequences of systemic lupus erythematosus (SLE) is lupus nephritis (LN). Visfatin, an adipokine that is significantly e...

Artificial Intelligence-Powered Molecular Docking and Steered Molecular Dynamics for Accurate scFv Selection of Anti-CD30 Chimeric Antigen Receptors.

Chimeric antigen receptor (CAR) T cells represent a revolutionary immunotherapy that allows specific tumor recognition by a unique single-chain fragme...

Improved prediction of anti-angiogenic peptides based on machine learning models and comprehensive features from peptide sequences.

Angiogenesis is a key process for the proliferation and metastatic spread of cancer cells. Anti-angiogenic peptides (AAPs), with the capability of inh...

Synthetically Feasible De Novo Molecular Design of Leads Based on a Reinforcement Learning Model: AI-Assisted Discovery of an Anti-IBD Lead Targeting CXCR4.

Artificial intelligence (AI) de novo molecular generation provides leads with novel structures for drug discovery. However, the target affinity and sy...

Machine learning models predicts risk of proliferative lupus nephritis.

OBJECTIVE: This study aims to develop and validate machine learning models to predict proliferative lupus nephritis (PLN) occurrence, offering a relia...

Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms.

Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid screening is the research focus of surface-enhanced ...

Prediction of Interactomic HUB Genes in Periodontitis With Acute Myocardial Infarction.

BACKGROUND: Acute myocardial infarction (AMI) risk correlates with C-reactive protein (CRP) levels, suggesting systemic inflammation is present well b...