AIMC Topic: Asthma
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Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation.
PloS one
Sep 5, 2023
The pectoralis muscle is an important indicator of respiratory muscle function and has been linked to various parenchymal biomarkers, such as airflow limitation severity and diffusing capacity for carbon monoxide, which are widely used in diagnosing ...
Home monitoring with connected mobile devices for asthma attack prediction with machine learning.
Scientific data
Jun 8, 2023
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...
Imaging-derived biomarkers in Asthma: Current status and future perspectives.
Respiratory medicine
Jan 23, 2023
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
Jan 19, 2023
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.
Children's views on artificial intelligence and digital twins for the daily management of their asthma: a mixed-method study.
European journal of pediatrics
Dec 13, 2022
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 ...
AsthmaKGxE: An asthma-environment interaction knowledge graph leveraging public databases and scientific literature.
Computers in biology and medicine
Aug 2, 2022
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...
Deep Learning for Automatic Upper Airway Obstruction Detection by Analysis of Flow-Volume Curve.
Respiration; international review of thoracic diseases
May 12, 2022
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 ...
S. aureus and IgE-mediated diseases: pilot or copilot? A narrative review.
Expert review of clinical immunology
May 9, 2022
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),...
Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.
BMC medical informatics and decision making
Apr 22, 2022
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...
Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization.
The Journal of asthma : official journal of the Association for the Care of Asthma
Apr 7, 2022
OBJECTIVE: Asthma is the most frequent chronic airway illness in preschool children and is difficult to diagnose due to the disease's heterogeneity. This study aimed to investigate different machine learning models and suggested the most effective on...
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