Allergy & Immunology

Allergy

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

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Allergy-Immunology Subcategories: Allergy
Showing 358-378 of 8,435 articles
Preliminary study on AI-assisted diagnosis of bone remodeling in chronic maxillary sinusitis.

OBJECTIVE: To construct the deep learning convolution neural network (CNN) model and machine learnin...

Preservative contact allergy in occupational dermatitis: a machine learning analysis.

Occupational dermatoses impose a significant socioeconomic burden. Allergic contact dermatitis relat...

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma.

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential...

Estimation of the amount of pear pollen based on flowering stage detection using deep learning.

Pear pollination is performed by artificial pollination because the pollination rate through insect ...

New vision of HookEfficientNet deep neural network: Intelligent histopathological recognition system of non-small cell lung cancer.

BACKGROUND: Efficient and precise diagnosis of non-small cell lung cancer (NSCLC) is quite critical ...

Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients.

BACKGROUND: The non-invasive biomarkers for predicting immunotherapy response are urgently needed to...

Predictive models and applicability of artificial intelligence-based approaches in drug allergy.

PURPOSE OF REVIEW: Drug allergy is responsible for a huge burden on public healthcare systems, repre...

Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma.

The functions of immunosenescence are closely related to skin cutaneous melanoma (SKCM). The aim of ...

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.

Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neo...

Identification of key genes and biological pathways associated with vascular aging in diabetes based on bioinformatics and machine learning.

Vascular aging exacerbates diabetes-associated vascular damage, a major cause of microvascular and m...

Local spatiotemporal dynamics of particulate matter and oak pollen measured by machine learning aided optical particle counters.

Conventional techniques for monitoring pollen currently have significant limitations in terms of lab...

Quantifying Nocturnal Scratch in Atopic Dermatitis: A Machine Learning Approach Using Digital Wrist Actigraphy.

Nocturnal scratching substantially impairs the quality of life in individuals with skin conditions s...

A novel machine learning model for efficacy prediction of immunotherapy-chemotherapy in NSCLC based on CT radiomics.

Lung cancer is categorized into two main types: non-small cell lung cancer (NSCLC) and small cell lu...

Identifying influence factors and thresholds of the next day's pollen concentration in different seasons using interpretable machine learning.

The prevalence of pollen allergies is a pressing global issue, with projections suggesting that half...

Machine learning in the prediction of immunotherapy response and prognosis of melanoma: a systematic review and meta-analysis.

BACKGROUND: The emergence of immunotherapy has changed the treatment modality for melanoma and prolo...

Comprehensive quantitative radiogenomic evaluation reveals novel radiomic subtypes with distinct immune pattern in glioma.

BACKGROUND: Accurate classification of gliomas is critical to the selection of immunotherapy, and MR...

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