AI Medical Compendium Topic

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Asthma

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

Expert review of clinical immunology
INTRODUCTION: is a major opportunistic pathogen that has been implicated in the pathogenesis of several chronic inflammatory diseases including bronchial asthma, chronic rhinosinusitis with nasal polyps (CRSwNP), chronic spontaneous urticaria (CSU),...

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

Respiration; international review of thoracic diseases
BACKGROUND: Due to the similar symptoms of upper airway obstruction to asthma, misdiagnosis is common. Spirometry is a cost-effective screening test for upper airway obstruction and its characteristic patterns involving fixed, variable intrathoracic ...

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

BMC medical informatics and decision making
BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future e...

Utilizing Deep Learning on Limited Mobile Speech Recordings for Detection of Obstructive Pulmonary Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Passive assessment of obstructive pulmonary disease has gained substantial interest over the past few years in the mobile and wearable computing communities. One of the promising approaches is speech-based pulmonary assessment wherein spontaneous or ...

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

Computers in biology and medicine
MOTIVATION: Asthma is a complex heterogeneous disease resulting from intricate interactions between genetic and non-genetic factors related to environmental and psychosocial aspects. Discovery of such interactions can provide insights into the pathop...

Children's views on artificial intelligence and digital twins for the daily management of their asthma: a mixed-method study.

European journal of pediatrics
New technologies enable the creation of digital twin systems (DTS) combining continuous data collection from children's home and artificial intelligence (AI)-based recommendations to adapt their care in real time. The objective was to assess whether ...

Imaging-derived biomarkers in Asthma: Current status and future perspectives.

Respiratory medicine
Asthma is a common disorder affecting around 315 million individuals worldwide. The heterogeneity of asthma is becoming increasingly important in the era of personalized treatment and response assessment. Several radiological imaging modalities are a...

Deep Learning-Based Segmentation of Airway Morphology from Endobronchial Optical Coherence Tomography.

Respiration; international review of thoracic diseases
BACKGROUND: Manual measurement of endobronchial optical coherence tomography (EB-OCT) images means a heavy workload in the clinical practice, which can also introduce bias if the subjective opinions of doctors are involved.

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

Scientific data
Monitoring asthma is essential for self-management. However, traditional monitoring methods require high levels of active engagement, and some patients may find this tedious. Passive monitoring with mobile-health devices, especially when combined wit...

Importance of GWAS Risk Loci and Clinical Data in Predicting Asthma Using Machine-learning Approaches.

Combinatorial chemistry & high throughput screening
INTRODUCTION: To understand the risk factors of asthma, we combined genome-wide association study (GWAS) risk loci and clinical data in predicting asthma using machine-learning approaches.