Extropy: Complementary Dual of Entropy

This article provides a completion to theories of information based on entropy, resolving a longstanding question in its axiomatization as proposed by Shannon and pursued by Jaynes. We show that Shannon's entropy function has a complementary dual function which we call "extropy." The entropy and the extropy of a binary distribution are identical. However, the measure bifurcates into a pair of distinct measures for any quantity that is not merely an event indicator. As with entropy, the maximum extropy distribution is also the uniform distribution, and both measures are invariant with respect to permutations of their mass functions. However, they behave quite differently in their assessments of the refinement of a distribution, the axiom which concerned Shannon and Jaynes. Their duality is specified via the relationship among the entropies and extropies of course and fine partitions. We also analyze the extropy function for densities, showing that relative extropy constitutes a dual to the Kullback-Leibler divergence, widely recognized as the continuous entropy measure. These results are unified within the general structure of Bregman divergences. In this context they identify half the $L_2$ metric as the extropic dual to the entropic directed distance. We describe a statistical application to the scoring of sequential forecast distributions which provoked the discovery.Comment: Published at http://dx.doi.org/10.1214/14-STS430 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Multitask Deep Learning for Accurate Risk Stratification and Prediction of Next Steps for Coronary CT Angiography Patients

Diagnostic investigation has an important role in risk stratification and clinical decision making of patients with suspected and documented Coronary Artery Disease (CAD). However, the majority of existing tools are primarily focused on the selection of gatekeeper tests, whereas only a handful of systems contain information regarding the downstream testing or treatment. We propose a multi-task deep learning model to support risk stratification and down-stream test selection for patients undergoing Coronary Computed Tomography Angiography (CCTA). The analysis included 14,021 patients who underwent CCTA between 2006 and 2017. Our novel multitask deep learning framework extends the state-of-the art Perceiver model to deal with real-world CCTA report data. Our model achieved an Area Under the receiver operating characteristic Curve (AUC) of 0.76 in CAD risk stratification, and 0.72 AUC in predicting downstream tests. Our proposed deep learning model can accurately estimate the likelihood of CAD and provide recommended downstream tests based on prior CCTA data. In clinical practice, the utilization of such an approach could bring a paradigm shift in risk stratification and downstream management. Despite significant progress using deep learning models for tabular data, they do not outperform gradient boosting decision trees, and further research is required in this area. However, neural networks appear to benefit more readily from multi-task learning than tree-based models. This could offset the shortcomings of using single task learning approach when working with tabular data

Comorbidity and repeat admission to hospital for adverse drug reactions in older adults: retrospective cohort study

Objectives To identify factors that predict repeat admission to hospital for adverse drug reactions (ADRs) in older adults

Investigating the User Experience of a Virtual Reality Rehabilitation Solution for a Biomechatronics Laboratory and Home Environment

publishedVersio

Under-ascertainment of Aboriginality in records of cardiovascular disease in hospital morbidity and mortality data in Western Australia: a record linkage study

<p>Abstract</p> <p>Background</p> <p>Measuring the real burden of cardiovascular disease in Australian Aboriginals is complicated by under-identification of Aboriginality in administrative health data collections. Accurate data is essential to measure Australia's progress in its efforts to intervene to improve health outcomes of Australian Aboriginals. We estimated the under-ascertainment of Aboriginal status in linked morbidity and mortality databases in patients hospitalised with cardiovascular disease.</p> <p>Methods</p> <p>Persons with public hospital admissions for cardiovascular disease in Western Australia during 2000-2005 (and their 20-year admission history) or who subsequently died were identified from linkage data. The Aboriginal status flag in all records for a given individual was variously used to determine their ethnicity (index positive, and in all records both majority positive or ever positive) and stratified by region, age and gender. The index admission was the baseline comparator.</p> <p>Results</p> <p>Index cases comprised 62,692 individuals who shared a total of 778,714 hospital admissions over 20 years, of which 19,809 subsequently died. There were 3,060 (4.9%) persons identified as Aboriginal on index admission. An additional 83 (2.7%) Aboriginal cases were identified through death records, increasing to 3.7% when cases with a positive Aboriginal identifier in the majority (≥50%) of previous hospital admissions over twenty years were added and by 20.8% when those with a positive flag in any record over 20 years were incorporated. These results equated to underestimating Aboriginal status in unlinked index admission by 2.6%, 3.5% and 17.2%, respectively. Deaths classified as Aboriginal in official records would underestimate total Aboriginal deaths by 26.8% (95% Confidence Interval 24.1 to 29.6%).</p> <p>Conclusions</p> <p>Combining Aboriginal determinations in morbidity and official death records increases ascertainment of unlinked cardiovascular morbidity in Western Australian Aboriginals. Under-identification of Aboriginal status is high in death records.</p

The relationship between abdominal pain and emotional wellbeing in children and adolescents in the Raine Study

Abdominal pain is a common reason for medical visits. We examined the prevalence, gastrointestinal, and emotional significance of abdominal pain in a population-based cohort serially followed up from birth to 17 years. Children and adolescents from Generation 2 of the Raine Study participated in comprehensive cross-sectional assessments at ages 2, 5, 8, 10, 14 and 17 years. At 17 years, medical history, general health, gastrointestinal symptoms, medications, health practitioner attendance, and self-rated unhappiness were recorded. Longitudinal data regarding abdominal pain or unhappiness, from serial questionnaires, were analysed to identify factors associated with abdominal pain and adverse emotional health at age 17 years. Females experienced more abdominal pain than males at all ages (p \u3c 0.05). Seventeen-year-old adolescents with abdominal pain reported a higher prevalence of depression, anxiety, being bullied at school, and poorer health status than those without abdominal pain (p \u3c 0.05 for all). Abdominal pain and unhappiness during childhood and mid-adolescence were prospectively associated with recurrent abdominal pain, anxiety, depression and unhappiness during late adolescence (p \u3c 0.05 for all). In conclusion, abdominal pain in children and adolescents associates with depression, anxiety, being bullied, unhappiness and reduced overall health-rating during adolescence. Awareness of these factors may guide management decisions

The relationship between abdominal pain and emotional wellbeing in children and adolescents in the Raine Study

Abdominal pain is a common reason for medical visits. We examined the prevalence, gastrointestinal, and emotional significance of abdominal pain in a population-based cohort serially followed up from birth to 17 years. Children and adolescents from Generation 2 of the Raine Study participated in comprehensive cross-sectional assessments at ages 2, 5, 8, 10, 14 and 17 years. At 17 years, medical history, general health, gastrointestinal symptoms, medications, health practitioner attendance, and self-rated unhappiness were recorded. Longitudinal data regarding abdominal pain or unhappiness, from serial questionnaires, were analysed to identify factors associated with abdominal pain and adverse emotional health at age 17 years. Females experienced more abdominal pain than males at all ages (p \u3c 0.05). Seventeen-year-old adolescents with abdominal pain reported a higher prevalence of depression, anxiety, being bullied at school, and poorer health status than those without abdominal pain (p \u3c 0.05 for all). Abdominal pain and unhappiness during childhood and mid-adolescence were prospectively associated with recurrent abdominal pain, anxiety, depression and unhappiness during late adolescence (p \u3c 0.05 for all). In conclusion, abdominal pain in children and adolescents associates with depression, anxiety, being bullied, unhappiness and reduced overall health-rating during adolescence. Awareness of these factors may guide management decisions

Needs and priority areas for building capacity for working with linked data in the Australian pharmacoepidemiology workforce

Introduction Linked data are increasingly used in pharmacoepidemiology studies to enhance value beyond that which can be achieve from stand-alone pharmaceutical data. The complexity of pharmaceutical data can make any linked data analysis challenging and it is imperative that this is matched by the human capacity to perform this work. Objectives and Approach Research is needed to understand the state of the current pharmacoepidemiology workforce and to prioritise its capacity building needs. We aim to profile the Australian pharmacoepidemiology workforce to explore views, needs, priority areas and perspectives relevant to capacity building. Participants are the regular pharmacoepidemiology workforce (Group 1) and senior medicines stakeholders (Group 2). Following a literature review and consultation with a group of key informants, we developed survey and interview instruments for each group. We piloted the instruments in February 2018 and study data collection is planned for March 2018. We will use a mixed-methods approach to analyse the data. Results We conducted a review of existing literature and identified workforce views, needs and priorities at four levels: personal, team, organisation and wider community. During the consultative process, the informants highlighted the multidisciplinary nature of the pharmacoepidemiology workforce including many with non-health related backgrounds. They also raised concerns about attracting applicants with suitable skills and experience, job satisfaction, career progression and workforce retention. We developed instruments to (i) further explore these issues, (ii) ascertain their experience with linked health data, (iii) determine their training needs, and, (iv) learn about their future intentions. We will present findings on issues pertinent to the Australian pharmacoepidemiology landscape and suggest priorities for building workforce capacity. Conclusion/Implications This study will provide empirical evidence to support and prioritise capacity building in the Australian pharmacoepidemiology workforce to improve their ability to work with linked data. The instruments that we developed and findings may be relevant to phamacoepidemiology workforce in other countries and other emerging fields that use linked data