Atopy

Pattern recognition of forced oscillation technique measurement results using deep learning can identify asthmatic patients more accurately than setting reference ranges.

No official clinical reference values have been established for MostGraph, which measures total respiratory resistance and reactance using the forced oscillation technique, complicating result interpretation. This study aimed to establish a reference range for MostGraph measurements and examine its usefulness in discriminating participants with asthma from controls (participants without any respir...

Machine Learning-Based Asthma Attack Prediction Models From Routinely Collected Electronic Health Records: Systematic Scoping Review.

BACKGROUND: An early warning tool to predict attacks could enhance asthma management and reduce the likelihood of serious consequences. Electronic health records (EHRs) providing access to historical data about patients with asthma coupled with machine learning (ML) provide an opportunity to develop such a tool. Several studies have developed ML-based tools to predict asthma attacks.

Prediction of the number of asthma patients using environmental factors based on deep learning algorithms.

BACKGROUND: Air pollution, weather, pollen, and influenza are typical aggravating factors for asthma. Previous studies have identified risk factors us...

Phosphorylated p38 MAP kinase expression by leucocytes is increased in allergic humans and associated with IgE responses.

Mitogen-activated protein kinases (MAPK) activate cascades that regulate cell proliferation, differentiation and death. Phosphorylated (phos-)p38 MAPK...

Hot topics in allergen immunotherapy, 2023: Current status and future perspective.

The importance of allergen immunotherapy (AIT) is multifaceted, encompassing both clinical and quality-of-life improvements and cost-effectiveness in ...

How AI is advancing asthma management? Insights into economic and clinical aspects.

Asthma, an increasingly prevalent chronic respiratory condition, incurs significant economic costs worldwide. Artificial Intelligence (AI), particular...

Untargeted metabolomic profiling in children identifies novel pathways in asthma and atopy.

BACKGROUND: Asthma and other atopic disorders can present with varying clinical phenotypes marked by differential metabolomic manifestations and enric...

The water-soluble subfraction from Artemisia argyi alleviates LPS-induced inflammatory responses via multiple pathways and targets in vitro and in vivo.

ETHNOPHARMACOLOGICAL RELEVANCE: As a traditional Chinese medicine, Artemisia argyi has been used medicinally and eaten for more than 2000 years in Chi...

An intronic genetic variant of ZHX2 predicts response to pegylated interferon α therapy in HBeAg-positive chronic hepatitis B patients.

ZHX2 plays a crucial role in host immunity and modulates hepatitis B virus (HBV) replication. However, its correlation with immunomodulator-related tr...

Correlation between serum 25(OH)D levels with severity of work-related hand eczema among healthcare workers: a cross-sectional study.

Hand eczema (HE) is a common condition seen in medical facilities, particularly during the COVID-19 pandemic. The effects of vitamin D on skin inflamm...

Artificial Intelligence Chatbot Shows Multiple Inaccuracies When Responding to Questions About Eosinophilic Esophagitis.

Predicting the therapeutic efficacy of AIT for asthma using clinical characteristics, serum allergen detection metrics, and machine learning techniques.

Bronchial asthma is a prevalent non-communicable disease among children. The study collected clinical data from 390 children aged 4-17 years with asth...

Unraveling the link between PTBP1 and severe asthma through machine learning and association rule mining method.

Severe asthma is a chronic inflammatory airway disease with great therapeutic challenges. Understanding the genetic and molecular mechanisms of severe...

COVID-19 diagnosis using clinical markers and multiple explainable artificial intelligence approaches: A case study from Ecuador.

The COVID-19 pandemic erupted at the beginning of 2020 and proved fatal, causing many casualties worldwide. Immediate and precise screening of affecte...

Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation.

The pectoralis muscle is an important indicator of respiratory muscle function and has been linked to various parenchymal biomarkers, such as airflow ...

Enhanced Deep Learning Approach for Accurate Eczema and Psoriasis Skin Detection.

This study presents an enhanced deep learning approach for the accurate detection of eczema and psoriasis skin conditions. Eczema and psoriasis are si...

Effects of secretome supplementation on interleukin-6, tumor necrosis factor-α, procalcitonin, and the length of stay in acute exacerbation COPD patients.

Acute exacerbation chronic obstructive pulmonary disease (AECOPD) is associated with significant poor survival. Mesenchymal stem cells (MSC) therapy h...

A Survey on Artificial Intelligence in Pulmonary Imaging.

Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and image recognition creating widespread opportunities o...

Home monitoring with connected mobile devices for asthma attack prediction with machine learning.

Monitoring asthma is essential for self-management. However, traditional monitoring methods require high levels of active engagement, and some patient...

Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model.

One of the important concerns in the field of exercise immunology is determining the appropriate intensity and duration of exercise to prevent suppres...