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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.

Decoding Susceptibility to Respiratory Viral Infections and Asthma Inception in Children

Human Respiratory Syncytial Virus and Human Rhinovirus are the most frequent cause of respiratory tract infections in infants and children and are major triggers of acute viral bronchiolitis, wheezing and asthma exacerbations.

WA researchers lead global centre to eliminate childhood asthma

An ambitious project that could stop children developing asthma is the centrepiece of a new world-class respiratory research centre launched in Perth.

Lung study helps history-making generation get a handle on their health

A lung function study carried out by Dr Shannon Simpson provided the most comprehensive follow-up of very pre-term children of any study so far carried out on the lung health of this vulnerable group.

ORIGINS Project shines light on Early Childhood Development

A collaboration between The Kids Research Institute Australia and Joondalup Health Campus is poised to be a game-changer for early childhood development.

Directing immune development to curb sky-rocketing disease

Once upon a time it was infectious diseases like polio, measles or tuberculosis that most worried parents. With these threats now largely under control, parents face a new challenge – sky-rocketing rates of non-infectious diseases such as asthma, allergies and autism.

Vitamin D over the first decade and susceptibility to childhood allergy and asthma

We aimed to research relationships between 25(OH)D levels from birth to 10 y/o and susceptibility to allergic sensitization, respiratory issues and asthma.

A genome-by-environment interaction classifier for precision medicine: personal transcriptome response to rhinovirus identifies children prone to asthma exacerbations

To introduce a disease prognosis framework enabled by a robust classification scheme derived from patient-specific transcriptomic response to stimulation.

Autism likelihood in infants born to mothers with asthma is associated with blood inflammatory gene biomarkers in pregnancy

Mothers with asthma or atopy have a higher likelihood of having autistic children, with maternal immune activation in pregnancy implicated as a mechanism. This study aimed to determine, in a prospective cohort of mothers with asthma and their infants, whether inflammatory gene expression in pregnancy is associated with likelihood of future autism. 

Respiratory infection- and asthma-prone, low vaccine responder children demonstrate distinct mononuclear cell DNA methylation pathways

nfants with frequent viral and bacterial respiratory infections exhibit compromised immunity to routine immunizations. They are also more likely to develop chronic respiratory diseases in later childhood. This study investigated the feasibility of epigenetic profiling to reveal endotype-specific molecular pathways with potential for early identification and immuno-modulation.