Psoriasis

Denoising: a powerful building block for imaging, inverse problems and machine learning.

Denoising, the process of reducing random fluctuations in a signal to emphasize essential patterns, has been a fundamental problem of interest since the dawn of modern scientific inquiry. Recent denoising techniques, particularly in imaging, have achieved remarkable success, nearing theoretical limits by some measures. Yet, despite tens of thousands of research papers, the wide-ranging application...

A primer on variational inference for physics-informed deep generative modelling.

Variational inference (VI) is a computationally efficient and scalable methodology for approximate Bayesian inference. It strikes a balance between accuracy of uncertainty quantification and practical tractability. It excels at generative modelling and inversion tasks due to its built-in Bayesian regularization and flexibility, essential qualities for physics-related problems. For such problems, t...

Bayesian computation with generative diffusion models by Multilevel Monte Carlo.

Generative diffusion models have recently emerged as a powerful strategy to perform stochastic sampling in Bayesian inverse problems, delivering remar...

Deep generative models for Bayesian inference on high-rate sensor data: applications in automotive radar and medical imaging.

Deep generative models (DGMs) have been studied and developed primarily in the context of natural images and computer vision. This has spurred the dev...

Fast 3D Room Layout Estimation Based on Compact High-Level Representation.

3D room layout estimation aims to reconstruct the holistic 3D structure from an indoor RGB image. For most of the deep learning-based methods, layout ...

Semantic Search of FDA Guidance Documents Using Generative AI.

INTRODUCTION: Generative artificial intelligence (AI) has the potential to transform and accelerate how information is accessed during the regulation ...

AbEpiTope-1.0: Improved antibody target prediction by use of AlphaFold and inverse folding.

B cell epitope prediction tools are crucial for designing vaccines and disease diagnostics. However, predicting which antigens a specific antibody bin...

Encoding flexible gait strategies in stick insects through data-driven inverse reinforcement learning.

Stick insects exhibit remarkable adaptive walking capabilities across diverse environments; however, the mechanisms underlying their gait transitions ...

Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for im...

Inverse Neural Network Approach for Optimizing Chemical Composition in Shielded Metal Arc Weld Metals.

This study presents a hybrid machine learning framework combining an artificial neural network and a genetic algorithm to optimize chemical compositio...

Hybrid Frameworks Integrating Deep Learning and Optimization Methods for Inverse Design in Nanophotonics.

Artificial intelligence (AI) has emerged as a transformative tool in nanophotonics, revolutionizing the field of inverse design of nanoscale devices. ...

Personalized dose reduction strategies for biologic disease-modifying antirheumatic drugs for treating axial spondyloarthritis: a clinical and economic evaluation with predictive modeling.

BACKGROUND: Axial spondyloarthritis (AS) is a chronic inflammatory disease that significantly affects quality of life and imposes a high economic burd...

Identification of PRKCQ-AS1 as a Keratinocyte-Derived Exosomal lncRNA That Promotes Th17 Differentiation and IL-17 secretion in Psoriasis Through Bioinformatics, Machine Learning Algorithms, and Cell Experiments.

BACKGROUND: Psoriasis is an immune-mediated skin disease where Th17 cell differentiation and IL-17 secretion play critical roles. This study investiga...

The Desmoid Dilemma: Challenges and Opportunities in Assessing Tumor Burden and Therapeutic Response.

Desmoid tumors are rare, locally invasive soft-tissue tumors with unpredictable clinical behavior. Imaging plays a crucial role in their diagnosis, me...

Combining Clinical, Genetic and Protein Markers Using Machine Learning Models Discriminates Psoriatic Arthritis Patients From Those With Psoriasis.

BACKGROUND: Psoriatic Arthritis (PsA), an immune mediated inflammatory arthritis, affects a quarter of patients with cutaneous psoriasis, usually afte...

Construction of Sonosensitizer-Drug Co-Assembly Based on Deep Learning Method.

Drug co-assemblies have attracted extensive attention due to their advantages of easy preparation, adjustable performance and drug component co-delive...

Therapeutic effect of systemic use of glatiramer acetate in imiquimod-induced mouse psoriasis model.

PURPOSE: The aim of this study is to evaluate the therapeutic potential of systemic glatiramer acetate (GA), a drug used in the treatment of multiple ...

Dapagliflozin targets the crosstalk between apoptosis, autophagy, and Hedgehog signaling pathways through AMPK activation in the adjuvant-induced arthritic rat model.

Rheumatoid arthritis is a long-term autoimmune disorder, causes joint capsule, cartilage, and bone damage. Dapagliflozin, a novel antidiabetic drug, d...

IL-17A, IL-17F, and IL-23 in Patients with Rheumatoid Arthritis.

The aim of the study was to determine the clinical and diagnostic value of IL-17A, IL-17F, and IL-23 in RA patients in the advanced stage of the disea...

A new kind of polystyrene/polyethyleneimine nanofibres coordinated with palladium for fast and efficient extraction of methotrexate and its polyglutamate metabolites in different matrices.

Methotrexate (MTX) is a drug that has long been used in high doses as an anti-cancer drug and lately in low doses as a treatment for autoimmune diseas...