Asthma

Biodegradable Smart Face Masks for Machine Learning-Assisted Chronic Respiratory Disease Diagnosis.

Utilizing smart face masks to monitor and analyze respiratory signals is a convenient and effective method to give an early warning for chronic respiratory diseases. In this work, a smart face mask is proposed with an air-permeable and biodegradable self-powered breath sensor as the key component. This smart face mask is easily fabricated, comfortable to use, eco-friendly, and has sensitive and st...

A Precision Health Service for Chronic Diseases: Development and Cohort Study Using Wearable Device, Machine Learning, and Deep Learning.

This paper presents an integrated and scalable precision health service for health promotion and chronic disease prevention. Continuous real-time monitoring of lifestyle and environmental factors is implemented by integrating wearable devices, open environmental data, indoor air quality sensing devices, a location-based smartphone app, and an AI-assisted telecare platform. The AI-assisted telecare...

AsthmaKGxE: An asthma-environment interaction knowledge graph leveraging public databases and scientific literature.

MOTIVATION: Asthma is a complex heterogeneous disease resulting from intricate interactions between genetic and non-genetic factors related to environ...

The effectiveness of gabapentin and gabapentin/montelukast combination compared with dextromethorphan in the improvement of COVID-19- related cough: A randomized, controlled clinical trial.

INTRODUCTION: Cough is one of the most common presenting symptoms of COVID-19, which can persist for weeks or months.

Deep Learning for Automatic Upper Airway Obstruction Detection by Analysis of Flow-Volume Curve.

BACKGROUND: Due to the similar symptoms of upper airway obstruction to asthma, misdiagnosis is common. Spirometry is a cost-effective screening test f...

Covariate adjustment of spirometric and smoking phenotypes: The potential of neural network models.

To increase power and minimize bias in statistical analyses, quantitative outcomes are often adjusted for precision and confounding variables using st...

S. aureus and IgE-mediated diseases: pilot or copilot? A narrative review.

INTRODUCTION: is a major opportunistic pathogen that has been implicated in the pathogenesis of several chronic inflammatory diseases including bronc...

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are...

Lightweight Long Short-Term Memory Variational Auto-Encoder for Multivariate Time Series Anomaly Detection in Industrial Control Systems.

Heterogeneous cyberattacks against industrial control systems (ICSs) have had a strong impact on the physical world in recent decades. Connecting devi...

Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization.

OBJECTIVE: Asthma is the most frequent chronic airway illness in preschool children and is difficult to diagnose due to the disease's heterogeneity. T...

A Three-Stage Dynamic Assessment Framework for Industrial Control System Security Based on a Method of W-HMM.

Industrial control systems (ICS) are applied in many fields. Due to the development of cloud computing, artificial intelligence, and big data analysis...

Effect Evaluation of Electronic Health PDCA Nursing in Treatment of Childhood Asthma with Artificial Intelligence.

Asthma in children has a long duration and is prone to recurring attacks. Children will feel chest tightness, shortness of breath, cough, and difficul...

Ethical Design and Use of Robotic Care of the Elderly.

The Australian Royal Commission into Aged Care Quality and Safety acknowledged understaffing and substandard care in residential aged care and home ca...

Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic Approach.

False alerts due to misconfigured or compromised intrusion detection systems (IDS) in industrial control system (ICS) networks can lead to severe econ...

Machine Vision and Intelligent Algorithm Based on Neural Network.

Neural network algorithms and intelligent algorithms are hot topics in the field of deep learning. In this study, the neural network algorithm and int...

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data.

Functional magnetic resonance imaging (fMRI) as a promising tool to investigate psychotic disorders can be decomposed into useful imaging features suc...

Combined Free-Energy Calculation and Machine Learning Methods for Understanding Ligand Unbinding Kinetics.

The determination of drug residence times, which define the time an inhibitor is in complex with its target, is a fundamental part of the drug discove...

Thermography based skin allergic reaction recognition by convolutional neural networks.

In this work we present an automated approach to allergy recognition based on neural networks. Allergic reaction classification is an important task i...

Specific IgE and IgG4 Profiles of House Dust Mite Components in Allergen-Specific Immunotherapy.

BACKGROUND: Allergen immunotherapy (AIT) can induce immune tolerance to allergens by activating multiple mechanisms, including promoting IgG4 synthesi...

Predicting Continuity of Asthma Care Using a Machine Learning Model: Retrospective Cohort Study.

Continuity of care (COC) has been shown to possess numerous health benefits for chronic diseases. Specifically, the establishment of its level can fac...