Allergy & Immunology

Multiomics Analysis of Disulfidptosis Patterns and Integrated Machine Learning to Predict Immunotherapy Response in Lung Adenocarcinoma.

BACKGROUND: Recent studies have unveiled disulfidptosis as a phenomenon intimately associated with c...

TEPCAM: Prediction of T-cell receptor-epitope binding specificity via interpretable deep learning.

The recognition of T-cell receptor (TCR) on the surface of T cell to specific epitope presented by t...

Importance of GWAS Risk Loci and Clinical Data in Predicting Asthma Using Machine-learning Approaches.

INTRODUCTION: To understand the risk factors of asthma, we combined genome-wide association study (G...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthc...

IgE anti-BP180 NC16A autoantibody in both serum and blister fluid samples does not correlate with disease activity of bullous pemphigoid.

The correlation between IgE anti-BP180 NC16A autoantibody and disease activity of bullous pemphigoid...

Artificial intelligence-assisted analysis for tumor-immune interaction within the invasive margin of colorectal cancer.

BACKGROUND: In colorectal cancer (CRC), both tumor invasion and immunological analysis at the tumor ...

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 ...

Automated and reproducible cell identification in mass cytometry using neural networks.

The principal use of mass cytometry is to identify distinct cell types and changes in their composit...

Efficacy and Tolerability of Tenofovir/Lamivudine/Dolutegravir among Antiretroviral Therapy Naive Human Immunodeficiency Virus Infected Patients of a Tertiary Care Center in Eastern India.

BACKGROUND: Although many drug regimens have been used in the treatment of human immunodeficiency vi...

Sputum Neutrophil Gelatinase-Associated Lipocalin as a Biomarker in Asthma-COPD Overlap.

BACKGROUND: Asthma COPD overlap (ACO) is a consensus-based phenotype having characteristics of both ...

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

Predictive overfitting in immunological applications: Pitfalls and solutions.

Overfitting describes the phenomenon where a highly predictive model on the training data generalize...

Long-term SARS-CoV-2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China.

The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people world...

Artificial intelligence in osteoarthritis: repair by knee joint distraction shows association of pain, radiographic and immunological outcomes.

OBJECTIVES: Knee joint distraction (KJD) has been associated with clinical and structural improvemen...

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...

Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA.

Ribonucleic acids (RNAs) play crucial roles in living organisms and some of them, such as bacterial ...

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 (...

Handling Class Imbalance in Machine Learning-based Prediction Models: A Case Study in Asthma Management.

A data-driven prediction tool has the potential to provide early warning of an asthma attack and imp...

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, ...