Asthma

Deep Neural Network for Respiratory Sound Classification in Wearable Devices Enabled by Patient Specific Model Tuning.

The primary objective of this paper is to build classification models and strategies to identify bre...

Artificial intelligence and machine learning in respiratory medicine.

: The application of artificial intelligence (AI) and machine learning (ML) in medicine and in parti...

A Machine-learning Approach to Forecast Aggravation Risk in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease with Clinical Indicators.

Patients with chronic obstructive pulmonary disease (COPD) repeat acute exacerbations (AE). Global I...

Rapid Detection From Clinical Mastitis Milk by Colloidal Gold Nanoparticle-Based Immunochromatographic Strips.

Rapid diagnostic technologies for bovine mastitis caused by () are urgently needed. In the current ...

A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data.

'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. R...

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...

Junctionless Poly-GeSn Ferroelectric Thin-Film Transistors with Improved Reliability by Interface Engineering for Neuromorphic Computing.

Ferroelectric HfZrO (Fe-HZO) with a larger remnant polarization () is achieved by using a poly-GeSn ...

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 ...

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 ...

All-Assay-Max2 pQSAR: Activity Predictions as Accurate as Four-Concentration ICs for 8558 Novartis Assays.

Profile-quantitative structure-activity relationship (pQSAR) is a massively multitask, two-step mach...

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...

Deep learning facilitates the diagnosis of adult asthma.

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

Do no harm: Natural language processing of social media supports safety of aseptic allergen immunotherapy procedures.

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 ...

Smooth Bayesian network model for the prediction of future high-cost patients with COPD.

INTRODUCTION: The clinical course of chronic obstructive pulmonary disease (COPD) is marked by acute...