Allergy

Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity.

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) ...

Deep learning-based high-throughput detection of in vitro germination to assess pollen viability from microscopic images.

In vitro pollen germination is considered the most efficient method to assess pollen viability. The ...

Pediatric Allergy and Immunology (PAI) is for polishing with artificial intelligence, but careful use.

DeepAlgPro: an interpretable deep neural network model for predicting allergenic proteins.

Allergies have become an emerging public health problem worldwide. The most effective way to prevent...

MITNet: a fusion transformer and convolutional neural network architecture approach for T-cell epitope prediction.

Classifying epitopes is essential since they can be applied in various fields, including therapeutic...

TCRmodel2: high-resolution modeling of T cell receptor recognition using deep learning.

The cellular immune system, which is a critical component of human immunity, uses T cell receptors (...

Immune Activation Modulation via Magnetically Localized Bacteria Based Micro/Bio Robot (BBMBR).

Understanding tumor's microenvironment is one of the key factors in the cancer therapy. Especially, ...

Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model.

MOTIVATION: Identifying the B-cell epitopes is an essential step for guiding rational vaccine develo...

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning.

We sought to determine whether machine learning and natural language processing (NLP) applied to ele...

Data-driven enzyme engineering to identify function-enhancing enzymes.

Identifying function-enhancing enzyme variants is a 'holy grail' challenge in protein science becaus...

Radiomic Models Predict Tumor Microenvironment Using Artificial Intelligence-the Novel Biomarkers in Breast Cancer Immune Microenvironment.

Breast cancer is the most common malignancy in women, and some subtypes are associated with a poor p...

Artificial Intelligence: An Emerging Intellectual Sword for Battling Carcinomas.

Artificial Intelligence (AI) is a branch of computer science that deals with mathematical algorithms...

Artificial intelligence and radiomics: fundamentals, applications, and challenges in immunotherapy.

Immunotherapy offers the potential for durable clinical benefit but calls into question the associat...

Single-frame 3D lensless microscopic imaging via deep learning.

Since the pollen of different species varies in shape and size, visualizing the 3-dimensional struct...

Substantive Interpretation of Machine Learning Solutions by the Example of Determining the Activity of the Tuberculosis Process in Individuals with Minimal Tuberculosis Residual Changes.

In this article is described an application of various machine learning (ML) methods to obtain decis...

Artificial Intelligence-based Radiomics in the Era of Immuno-oncology.

The recent, rapid advances in immuno-oncology have revolutionized cancer treatment and spurred furth...

Utilizing Deep Learning to Analyze Whole Slide Images of Colonic Biopsies for Associations Between Eosinophil Density and Clinicopathologic Features in Active Ulcerative Colitis.

BACKGROUND: Eosinophils have been implicated in the pathogenesis of ulcerative colitis and have been...

ImmuneData: an integrated data discovery system for immunology data repositories.

UNLABELLED: To meet the increasing demand for data sharing, data reuse and meta-analysis in the immu...

Comprehensive Prediction of Lipocalin Proteins Using Artificial Intelligence Strategy.

BACKGROUND: Lipocalin belongs to the calcyin family, and its sequence length is generally between 16...

epitope3D: a machine learning method for conformational B-cell epitope prediction.

The ability to identify antigenic determinants of pathogens, or epitopes, is fundamental to guide ra...

Predicting antibody binders and generating synthetic antibodies using deep learning.

The antibody drug field has continually sought improvements to methods for candidate discovery and e...