Search
Research
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.
Research
Conducting decolonizing research and practice with Australian First Nations to close the health gapThe purpose of this paper is to highlight a perspective for decolonizing research with Australian First Nations and provide a framework for successful and sustained knowledge translation by drawing on the recent work conducted by a research group, in five remote communities in North-Western Australia.
Research
BEAT CF pulmonary exacerbations core protocol for evaluating the management of pulmonary exacerbations in people with cystic fibrosisCystic fibrosis (CF) is a rare, inherited, life-limiting condition predominantly affecting the lungs, for which there is no cure. The disease is characterized by recurrent pulmonary exacerbations (PEx), which are thought to drive progressive lung damage. Management of these episodes is complex and generally involves multiple interventions targeting different aspects of disease. The emergence of innovative trials and use of Bayesian statistical methods has created renewed opportunities for studying heterogeneous populations in rare diseases.
Research
Learning to make a difference for chILD: Value creation through network collaboration and team scienceAddressing the recognized challenges and inequalities in providing high quality healthcare for rare diseases such as children's interstitial lung disease (chILD) requires collaboration across institutional, geographical, discipline, and system boundaries. The Children's Interstitial Lung Disease Respiratory Network of Australia and New Zealand (chILDRANZ) is an example of a clinical network that brings together multidisciplinary health professionals for collaboration, peer learning, and advocacy with the goal of improving the diagnosis and management of this group of rare and ultra-rare conditions.
Research
Genome Sequence of a Lytic Staphylococcus aureus Bacteriophage Isolated from Breast MilkWe identified a double-stranded DNA (dsDNA) bacteriophage appearing to belong to Herelleviridae, genus Kayvirus. The bacteriophage, Biyabeda-mokiny 1, was isolated from breast milk using a clinical isolate of Staphylococcus aureus.