Allergy & Immunology

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

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Showing 379-399 of 5,393 articles
Identification of diagnostic biomarkers and molecular subtype analysis associated with m6A in Tuberculosis immunopathology using machine learning.

Tuberculosis (TB), ranking just below COVID-19 in global mortality, is a highly complex infectious d...

Accurate Airway Tree Segmentation in CT Scans via Anatomy-Aware Multi-Class Segmentation and Topology-Guided Iterative Learning.

Intrathoracic airway segmentation in computed tomography is a prerequisite for various respiratory d...

Integrated multi-omics and machine learning reveal a gefitinib resistance signature for prognosis and treatment response in lung adenocarcinoma.

Gefitinib resistance (GR) presents a significant challenge in treating lung adenocarcinoma (LUAD), h...

The role of artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis.

Immune checkpoint inhibitors (ICIs) are revolutionizing cancer treatment, and Artificial Intelligenc...

Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy.

BACKGROUND: Lung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and...

Potential diagnostic biomarkers in heart failure: Suppressed immune-associated genes identified by bioinformatic analysis and machine learning.

Heart failure (HF) threatens tens of millions of people's health worldwide, which is the terminal st...

Predicting Asthma Exacerbations Using Machine Learning Models.

INTRODUCTION: Although clinical, functional, and biomarker data predict asthma exacerbations, newer ...

Machine learning identifies immune-based biomarkers that predict efficacy of anti-angiogenesis-based therapies in advanced lung cancer.

BACKGROUND: The anti-angiogenic drugs showed remarkable efficacy in the treatment of lung cancer. No...

Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis.

BACKGROUND: Asthma exacerbations in children pose a significant burden on healthcare systems and fam...

Identification of TXN and F5 as novel diagnostic gene biomarkers of the severe asthma based on bioinformatics and machine learning analysis.

Asthma poses a major threat to human health. The aim of this study was to identify genetic markers o...

Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy.

Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability...

Predicting and Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence in Pancreatic Cancer.

Pancreatic cancer remains one of the most lethal cancers, primarily due to its late diagnosis and li...

Machine Learning-enhanced Signature of Metastasis-related T Cell Marker Genes for Predicting Overall Survival in Malignant Melanoma.

In this study, we aimed to investigate disparities in the tumor immune microenvironment (TME) betwee...

Bacterial profile-based body fluid identification using a machine learning approach.

BACKGROUND: Identifying the origins of biological traces is critical for the reconstruction of crime...

Automated real-world data integration improves cancer outcome prediction.

The digitization of health records and growing availability of tumour DNA sequencing provide an oppo...

Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.

This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infectio...

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