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OBJECTIVES Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes. SETTING A regional cancer centre in Australia.(More)
BACKGROUND Selective serotonin reuptake inhibitors (SSRIs) are widely used antidepressants and one of the most commonly used medications. There is growing concern that SSRIs, which sequester in bone marrow at higher concentrations than brain or blood, increase bone fragility and fracture risk. However, their mechanism of action on human osteoclasts (OC) and(More)
Feature engineering is a time consuming component of predictive modeling. We propose a versatile platform to automatically extract features for risk prediction, based on a pre-defined and extensible entity schema. The extraction is independent of disease type or risk prediction task. We contrast auto-extracted features to baselines generated from the(More)
BACKGROUND To date, our ability to accurately identify patients at high risk from suicidal behaviour, and thus to target interventions, has been fairly limited. This study examined a large pool of factors that are potentially associated with suicide risk from the comprehensive electronic medical record (EMR) and to derive a predictive model for 1-6 month(More)
Previous research has shown that player involvement can be influenced by a range of factors, from the controllers used to the perceived level of challenge provided by the game. However, little attention has been paid to the influence of the game interface. Game interfaces consist of both diegetic (that can be viewed by the player-character, e.g. the game(More)
A hypoglycemia-induced fall is common in older persons with diabetes. The etiology of falls in this population is usually multifactorial, and includes microvascular and macrovascular complications and age-related comorbidities, with hypoglycemia being one of the major precipitating causes. In this review, we systematically searched the literature that was(More)
Macrophage apoptosis, a key process in atherogenesis, is regulated by oxidation products, including hydroxyoctadecadienoic acids (HODEs). These stable oxidation products of linoleic acid (LA) are abundant in atherosclerotic plaque and activate PPARγ and GPR132. We investigated the mechanisms through which HODEs regulate apoptosis. The effect of HODEs on(More)
Selective serotonin reuptake inhibitors (SSRIs) are the most commonly prescribed treatments for depression and, as a class of drugs, are among the most used medications in the world. Concern regarding possible effects of SSRI treatment on fetal development has arisen recently as studies have suggested a link between maternal SSRI use and an increase in(More)
BACKGROUND Gestational Diabetes Mellitus (GDM) has well recognised adverse health implications for the mother and her newborn that are both short and long term. Obesity is a significant risk factor for developing GDM and the prevalence of obesity is increasing globally. It is a matter of public health importance that clinicians have evidence based(More)
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