Allergy & Immunology

Latest AI and machine learning research in allergy & immunology for healthcare professionals.

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Integrated machine learning to predict the prognosis of lung adenocarcinoma patients based on SARS-COV-2 and lung adenocarcinoma crosstalk genes.

Viruses are widely recognized to be intricately associated with both solid and hematological maligna...

A Multi-model Deep Learning Architecture for Diagnosing Multi-class Skin Diseases.

Skin diseases are a significant global public health concern, affecting 21-85% of the world's popula...

Machine learning models reveal ARHGAP11A's impact on lymph node metastasis and stemness in NSCLC.

Most patients with non-small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the dise...

Alg-MFDL: A multi-feature deep learning framework for allergenic proteins prediction.

The escalating global incidence of allergy patients illustrates the growing impact of allergic issue...

Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG.

This work reports an efficient method to detect SARS-CoV-2 antibodies in blood samples based on SERS...

Recent Advances in Artificial Intelligence to Improve Immunotherapy and the Use of Digital Twins to Identify Prognosis of Patients with Solid Tumors.

To date, the public health system has been impacted by the increasing costs of many diagnostic and t...

Optimizing lipid nanoparticles for fetal gene delivery in vitro, ex vivo, and aided with machine learning.

There is a clinical need to develop lipid nanoparticles (LNPs) to deliver congenital therapies to th...

Machine learning-based new classification for immune infiltration of gliomas.

BACKGROUND: Glioma is a highly heterogeneous and poorly immunogenic malignant tumor, with limited ef...

Imaging pollen using a Raspberry Pi and LED with deep learning.

The production of low-cost, small footprint imaging sensor would be invaluable for airborne global m...

Future of allergy and immunology: Is artificial intelligence the key in the digital era?

Artificial intelligence (AI) is reshaping allergy and immunology by integrating cutting-edge technol...

Towards novel small-molecule inhibitors blocking PD-1/PD-L1 pathway: From explainable machine learning models to molecular dynamics simulation.

Molecular design of small-molecule inhibitors targeting programmed cell death-1 (PD-1)/programmed ce...

Real-time monitoring of single dendritic cell maturation using deep learning-assisted surface-enhanced Raman spectroscopy.

Dynamic real-time detection of dendritic cell (DC) maturation is pivotal for accurately predicting ...

Assessing prospective molecular biomarkers and functional pathways in severe asthma based on a machine learning method and bioinformatics analyses.

BACKGROUND: Severe asthma, which differs significantly from typical asthma, involves specific molecu...

Integrative multi-omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma.

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to th...

A preliminary review of the utility of artificial intelligence to detect eosinophilic chronic rhinosinusitis.

While typically diagnosed with biopsy, ECRS may be predicted preoperatively with the use of AI. Vari...

Parameter optimization for stable clustering using FlowSOM: a case study from CyTOF.

High-dimensional cell phenotyping is a powerful tool to study molecular and cellular changes in heal...

Tracing the path from preschool wheezing to asthma.

This short review illustrates, using two recent studies, the potential and challenges of using machi...

Prediction of Crohn's disease based on deep feature recognition.

BACKGROUND: Crohn's disease is a complex genetic disease that involves chronic gastrointestinal infl...

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