AIMC Topic: Asthma
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Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach.
BMC medical research methodology
Mar 29, 2019
BACKGROUND: Chronic respiratory symptoms involving bronchitis, cough and phlegm in children are underappreciated but pose a significant public health burden. Efforts for prevention and management could be supported by an understanding of the relative...
netDx: interpretable patient classification using integrated patient similarity networks.
Molecular systems biology
Mar 14, 2019
Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse da...
Demographic, Clinical, and Allergic Characteristics of Children with Eosinophilic Esophagitis in Isfahan, Iran.
Iranian journal of allergy, asthma, and immunology
Dec 3, 2018
Eosinophilic esophagitis (EoE) is a chronic immune-mediated disease isolated to the esophagus Food allergy is thought to play an important role in the pathophysiology of EOE. The aim of this study is to evaluate demographic features and sensitivity o...
Machine learning to identify pairwise interactions between specific IgE antibodies and their association with asthma: A cross-sectional analysis within a population-based birth cohort.
PLoS medicine
Nov 13, 2018
BACKGROUND: The relationship between allergic sensitisation and asthma is complex; the data about the strength of this association are conflicting. We propose that the discrepancies arise in part because allergic sensitisation may not be a single ent...
Characterization and classification of asthmatic wheeze sounds according to severity level using spectral integrated features.
Computers in biology and medicine
Nov 2, 2018
OBJECTIVE: This study aimed to investigate and classify wheeze sounds of asthmatic patients according to their severity level (mild, moderate and severe) using spectral integrated (SI) features.
Machine learning approaches for predicting disposition of asthma and COPD exacerbations in the ED.
The American journal of emergency medicine
Jun 28, 2018
OBJECTIVE: The prediction of emergency department (ED) disposition at triage remains challenging. Machine learning approaches may enhance prediction. We compared the performance of several machine learning approaches for predicting two clinical outco...
Predicted airway obstruction distribution based on dynamical lung ventilation data: A coupled modeling-machine learning methodology.
International journal for numerical methods in biomedical engineering
Jun 26, 2018
In asthma and chronic obstructive pulmonary disease, some airways of the tracheobronchial tree can be constricted, from moderate narrowing up to closure. Those pathological patterns of obstructions affect the lung ventilation distribution. While some...
Identification of differentially expressed genes associated with asthma in children based on the bioanalysis of the regulatory network.
Molecular medicine reports
Jun 22, 2018
Asthma, the most common chronic respiratory tract disease in children, is characterized by allergy, recurring airway obstruction and bronchospasm. The aim of the present study was to screen critical differentially expressed genes (DEGs) involved in a...
A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data.
Scientific reports
Jun 11, 2018
Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal sam...
Modeling asynchronous event sequences with RNNs.
Journal of biomedical informatics
Jun 5, 2018
Sequences of events have often been modeled with computational techniques, but typical preprocessing steps and problem settings do not explicitly address the ramifications of timestamped events. Clinical data, such as is found in electronic health re...
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