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Does machine learning have a role in the prediction of asthma in children?Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide effort to develop tools/methods to identify children's risk for asthma as early as possible for preventative and early management strategies. Unfortunately, most childhood asthma prediction tools using conventional statistical models have modest accuracy, sensitivity, and positive predictive value.
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Effects of human rhinovirus on epithelial barrier integrity and function in children with asthmaThis study demonstrates novel intrinsic differences in tight junctions gene and protein expression between airway epithelial cells of children with and without asthma
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Clinical characteristics of eosinophilic asthma exacerbationsEosinophilic asthma exacerbations may be clinically more severe than non-eosinophilic exacerbation
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Distinguishing benign from pathologic TH2 immunity in atopic childrenIn addition to its role in blocking TH2 effector activation in the late-phase allergic response, IL-10 is a known IgG1 switch factor
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Pressurised metered dose inhaler-spacer technique in young children improves with video instructionRepeated video instruction over time improves inhaler technique in young children
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Disruption of β-catenin/CBP signaling inhibits human airway epithelial-mesenchymal transition and repair.The airway epithelium of both children and adults with asthma is relatively undifferentiated characterized by a significantly increased proportion of...
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Environmental Factors in Children's Asthma and Respiratory EffectsAsthma is more common in childhood than in adulthood and is more correctly thought of as a syndrome than as a discrete condition.
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AsthmaOne in eight children have asthma, a chronic disease of the airways in the lungs. It results in shortness of breath, chest tightness, wheezing and coughing.
News & Events
Reducing the asthma burden: generous grant secured to develop world-first treatmentResearchers developing a world-first treatment that targets an underlying cause of asthma have secured a $499,640 grant from the Future Health, Research and Innovation Fund – Innovation Seed Fund.
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Airway-associated adipose tissue accumulation is increased in a kisspeptin receptor knockout mouse modelAirway-associated adipose tissue increases with body mass index and is a local source of pro-inflammatory adipokines that may contribute to airway pathology in asthma co-existing with obesity. Genetic susceptibility to airway adiposity was considered in the present study through kisspeptin/kisspeptin receptor signalling, known to modulate systemic adiposity and potentially drive airway remodelling.