Allergy & Immunology

Allergy

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

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Allergy-Immunology Subcategories: Allergy
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Precise Pollen Grain Detection in Bright Field Microscopy Using Deep Learning Techniques.

The determination of daily concentrations of atmospheric pollen is important in the medical and biol...

Safety of viable embryonated eggs of the whipworm as a novel food pursuant to Regulation (EU) 2015/2283.

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food ...

Future of Radiotherapy in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as asso...

Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters.

Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant tr...

Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data.

Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the ris...

IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatment.

Wart disease (WD) is a skin illness on the human body which is caused by the human papillomavirus (H...

Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Pollen.

Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, ...

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.

Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptio...

Data augmentation in dermatology image recognition using machine learning.

BACKGROUND: Each year in the United States, over 80 million people are affected by acne, atopic derm...

Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides.

BACKGROUND: Targeting epitopes derived from neo-antigens (or "neo-epitopes") represents a promising ...

Quantitative Prediction of the Landscape of T Cell Epitope Immunogenicity in Sequence Space.

Immunodominant T cell epitopes preferentially targeted in multiple individuals are the critical elem...

ELM-MHC: An Improved MHC Identification Method with Extreme Learning Machine Algorithm.

The major histocompatibility complex (MHC) is a term for all gene groups of a major histocompatibili...

Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data.

PURPOSE: Cancers are almost always diagnosed by morphologic features in tissue sections. In this con...

Application of adaptive-network-based fuzzy inference systems to the parameter optimization of a biochemical rule-based model.

In this study, the binding of allergens to antibody-receptor complexes was investigated. This proces...

Deep learning for DNase I hypersensitive sites identification.

BACKGROUND: The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA eleme...

Ceftaroline Fosamil as an Alternative for a Severe Methicillin-resistant Staphylococcus aureus Infection: A Case Report.

Bacteremia secondary to methicillin-resistant Staphylococcus aureus (MRSA) is a dreaded medical cond...

Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine.

Atopic dermatitis (AD) is a complex multifactorial inflammatory skin disease that affects ~280 milli...

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