Dermatology

Atopy

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

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Dermatology Subcategories: Atopy Psoriasis
Showing 253-273 of 3,566 articles
A comparative study of machine learning classifiers for risk prediction of asthma disease.

Asthma is a chronic disease characterized by wheezing, chest tightening and difficulty in breathing ...

Prodromal clinical, demographic, and socio-ecological correlates of asthma in adults: a 10-year statewide big data multi-domain analysis.

To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and...

Predicting asthma attacks in primary care: protocol for developing a machine learning-based prediction model.

INTRODUCTION: Asthma is a long-term condition with rapid onset worsening of symptoms ('attacks') whi...

Using machine learning to examine the relationship between asthma and absenteeism.

In this study, we found that machine learning was able to effectively estimate student learning outc...

Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection.

BACKGROUND AND OBJECTIVE: Wheezing is a common symptom of patients caused by asthma and chronic obst...

Self-Paced Balance Learning for Clinical Skin Disease Recognition.

Class imbalance is a challenging problem in many classification tasks. It induces biased classificat...

Deep learning facilitates the diagnosis of adult asthma.

BACKGROUND: We explored whether the use of deep learning to model combinations of symptom-physical s...

An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning.

Approximately 300 million people are afflicted with asthma around the world, with the estimated deat...

Novel pediatric-automated respiratory score using physiologic data and machine learning in asthma.

OBJECTIVES: Manual clinical scoring systems are the current standard used for acute asthma clinical ...

netDx: interpretable patient classification using integrated patient similarity networks.

Patient classification has widespread biomedical and clinical applications, including diagnosis, pro...

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...

Demographic, Clinical, and Allergic Characteristics of Children with Eosinophilic Esophagitis in Isfahan, Iran.

Eosinophilic esophagitis (EoE) is a chronic immune-mediated disease isolated to the esophagus Food a...

A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospita...

Dynamic changes in specific anti-L-asparaginase antibodies generation during acute lymphoblastic leukemia treatment.

BACKGROUND: L-asparaginase (L-asp) remains one of the key components of acute lymphoblastic leukemia...

Versatility of fuzzy logic in chronic diseases: A review.

The review aims at providing current state of evidence in the field of medicine with fuzzy logic for...

Specific and sensitive ELISA for measurement of IgE-binding variations of milk allergen β-lactoglobulin in processed foods.

Immunochemical detection of food allergens is usually based on the use of polyclonal or monoclonal i...

Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods.

We investigated whether machine learning methods could potentially identify a subgroup of persons wi...

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