Atopy

Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consen...

Vitamin D and Serum Immunoglobulin E Levels in Allergic Rhinitis: A Case-control Study from Pakistan.

Introduction Allergic rhinitis (AR) is the most common non-infectious rhinitis and is associated wit...

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

The wide adoption of electronic health record systems in health care generates big real-world data t...

The doctor will see you now: How machine learning and artificial intelligence can extend our understanding and treatment of asthma.

Machine learning approach to single nucleotide polymorphism-based asthma prediction.

Machine learning (ML) is poised as a transformational approach uniquely positioned to discover the h...

Inverse association between infection and childhood asthma in Greece: a case-control study.

INTRODUCTION: infection is a well-established etiological factor for a variety of diseases such as ...

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma.

BACKGROUND: Predictive modeling with longitudinal electronic health record (EHR) data offers great p...

Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry.

Imaging flow cytometry (IFC) produces up to 12 spectrally distinct, information-rich images of singl...

White blood cells detection and classification based on regional convolutional neural networks.

White blood cells (WBC) are important parts of our immune system and they protect our body against i...

Excitation Emission Matrix Fluorescence Spectroscopy for Combustion Generated Particulate Matter Source Identification.

The inhalation of particulate matter (PM) is a significant health risk associated with reduced life ...

Dehydroepiandrosterone Supplementation May Benefit Women with Asthma Who Have Low Androgen Levels: A Pilot Study.

INTRODUCTION: Among individuals with severe asthma, FEV is low in individuals with low dehydroepiand...

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...