Allergy & Immunology

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

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Showing 820-840 of 5,423 articles
Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-ch...

Deep Learning Algorithms-Based CT Images in Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction.

CT image information data under deep learning algorithms was adopted to evaluate small airway functi...

Correlation of serum microRNA-122 level with the levels of Alanine aminotransferase and HBV-DNA in Chronic HBV-infected patients.

The microRNA-122 (miR-122) is a liver-specific microRNA that can be used as a potential molecular m...

Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy.

Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and ide...

Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.

Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that requires e...

Explainable Molecular Sets: Using Information Theory to Generate Meaningful Descriptions of Groups of Molecules.

Algorithmically identifying the meaningful similarities between an assortment of molecules is a crit...

Stem-cell based, machine learning approach for optimizing natural killer cell-based personalized immunotherapy for high-grade ovarian cancer.

Advanced high-grade serous ovarian cancer continues to be a therapeutic challenge for those affected...

DMFMDA: Prediction of Microbe-Disease Associations Based on Deep Matrix Factorization Using Bayesian Personalized Ranking.

Identifying the microbe-disease associations is conducive to understanding the pathogenesis of disea...

Automation of penicillin adverse drug reaction categorisation and risk stratification with machine learning natural language processing.

BACKGROUND: The penicillin adverse drug reaction (ADR) label is common in electronic health records ...

Risk factor assessments of temporomandibular disorders via machine learning.

This study aimed to use artificial intelligence to determine whether biological and psychosocial fac...

Rapid, label-free classification of tumor-reactive T cell killing with quantitative phase microscopy and machine learning.

Quantitative phase microscopy (QPM) enables studies of living biological systems without exogenous l...

T Cell Epitope Prediction and Its Application to Immunotherapy.

T cells play a crucial role in controlling and driving the immune response with their ability to dis...

Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning.

Particle agglutination assays are widely adopted immunological tests that are based on antigen-antib...

Diagnostic classification of coronavirus disease 2019 (COVID-19) and other pneumonias using radiomics features in CT chest images.

We propose a classification method using the radiomics features of CT chest images to identify patie...

Applying interpretable deep learning models to identify chronic cough patients using EHR data.

BACKGROUND AND OBJECTIVE: Chronic cough (CC) affects approximately 10% of adults. Many disease state...

Deep Learning-Based High-Frequency Ultrasound Skin Image Classification with Multicriteria Model Evaluation.

This study presents the first application of convolutional neural networks to high-frequency ultraso...

Development of a gold-nanorod-based lateral flow immunoassay for a fast and dual-modal detection of C-reactive protein in clinical plasma samples.

Fast and simple detection of C-reactive protein (CRP) is highly significant for the diagnosis and pr...

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitativ...

Deep learning-based detection of eosinophilic esophagitis.

BACKGROUND: For eosinophilic esophagitis (EoE), a substantial diagnostic delay is still a clinically...

NIgPred: Class-Specific Antibody Prediction for Linear B-Cell Epitopes Based on Heterogeneous Features and Machine-Learning Approaches.

Upon invasion by foreign pathogens, specific antibodies can identify specific foreign antigens and d...

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