Latest AI and machine learning research in allergy & immunology for healthcare professionals.
While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen presentation by human leukocyte antigen (HLA) class II molecules remains a challenge. This identification is critical for developing vaccines and cancer immunotherapies. Current prediction methods are limited, primarily due to a lack of high-quality t...
To identify disease signature genes associated with immune infiltration in nonalcoholic steatohepatitis (NASH), we downloaded 2 publicly available gene expression profiles, GSE164760 and GSE37031, from the gene expression omnibus database. These profiles represent human NASH and control samples and were used for differential genes (DEGs) expression screening. Two machine learning methods, the Leas...
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demons...
BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in children. However, distinguishing GAS from viral phary...
The U.S. Government is committed to maintaining a robust research program that supports a portfolio of scientific experts who are investigating the bi...
BACKGROUND: Allergic rhinitis constitutes a widespread health concern, with traditional treatments often proving to be painful and ineffective. Acupun...
A powerful adaptive immune system, which includes cellular (T lymphocytes) and humoral (B lymphocytes) immunity, depends on its ability to recognize a...
BACKGROUND: Optimal management of allergic rhinitis requires patient education with easy access to accurate information. However, previous online plat...
OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarbox...
This perspective delves into the integration of artificial intelligence (AI) to enhance early diagnosis in hidradenitis suppurativa (HS). Despite sign...
UNLABELLED: Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunotherapy response. However, quantification of PD-L1 sta...
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enab...
BACKGROUND: Corneocyte surface nanoscale topography (nanotexture) has recently emerged as a potential biomarker for inflammatory skin diseases, such a...
While there is a growing recognition of the association between depression and asthma, few studies have leveraged deep learning-based (DL-based) model...
Addressing the challenge of cost-effective asthma diagnosis amidst diverse symptom patterns among patients, this study aims to develop a machine lear...
Artificial intelligence (AI) is certainly going to have a large, potentially huge, impact on the practice of family medicine. The specialty is fortuna...
INTRODUCTION: To understand the risk factors of asthma, we combined genome-wide association study (GWAS) risk loci and clinical data in predicting ast...
The recognition of T-cell receptor (TCR) on the surface of T cell to specific epitope presented by the major histocompatibility complex is the key to ...
BACKGROUND: Recent studies have unveiled disulfidptosis as a phenomenon intimately associated with cellular damage, heralding new avenues for explorin...