29 research outputs found

    Finite-sample and asymptotic sign-based tests for parameters of non-linear quantile regression with Markov noise

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    One of the most noticeable features of sign-based statistical procedures is an opportunity to build an exact test for simple hypothesis testing of parameters in a regression model. In this article, we expanded a sing-based approach to the nonlinear case with dependent noise. The examined model is a multi-quantile regression, which makes it possible to test hypothesis not only of regression parameters, but of noise parameters as well

    Neural networks for genetic epidemiology: past, present, and future

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    During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN) are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes

    Efficacy of self-monitored blood pressure, with or without telemonitoring, for titration of antihypertensive medication (TASMINH4): an unmasked randomised controlled trial.

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    BACKGROUND: Studies evaluating titration of antihypertensive medication using self-monitoring give contradictory findings and the precise place of telemonitoring over self-monitoring alone is unclear. The TASMINH4 trial aimed to assess the efficacy of self-monitored blood pressure, with or without telemonitoring, for antihypertensive titration in primary care, compared with usual care. METHODS: This study was a parallel randomised controlled trial done in 142 general practices in the UK, and included hypertensive patients older than 35 years, with blood pressure higher than 140/90 mm Hg, who were willing to self-monitor their blood pressure. Patients were randomly assigned (1:1:1) to self-monitoring blood pressure (self-montoring group), to self-monitoring blood pressure with telemonitoring (telemonitoring group), or to usual care (clinic blood pressure; usual care group). Randomisation was by a secure web-based system. Neither participants nor investigators were masked to group assignment. The primary outcome was clinic measured systolic blood pressure at 12 months from randomisation. Primary analysis was of available cases. The trial is registered with ISRCTN, number ISRCTN 83571366. FINDINGS: 1182 participants were randomly assigned to the self-monitoring group (n=395), the telemonitoring group (n=393), or the usual care group (n=394), of whom 1003 (85%) were included in the primary analysis. After 12 months, systolic blood pressure was lower in both intervention groups compared with usual care (self-monitoring, 137·0 [SD 16·7] mm Hg and telemonitoring, 136·0 [16·1] mm Hg vs usual care, 140·4 [16·5]; adjusted mean differences vs usual care: self-monitoring alone, -3·5 mm Hg [95% CI -5·8 to -1·2]; telemonitoring, -4·7 mm Hg [-7·0 to -2·4]). No difference between the self-monitoring and telemonitoring groups was recorded (adjusted mean difference -1·2 mm Hg [95% CI -3·5 to 1·2]). Results were similar in sensitivity analyses including multiple imputation. Adverse events were similar between all three groups. INTERPRETATION: Self-monitoring, with or without telemonitoring, when used by general practitioners to titrate antihypertensive medication in individuals with poorly controlled blood pressure, leads to significantly lower blood pressure than titration guided by clinic readings. With most general practitioners and many patients using self-monitoring, it could become the cornerstone of hypertension management in primary care. FUNDING: National Institute for Health Research via Programme Grant for Applied Health Research (RP-PG-1209-10051), Professorship to RJM (NIHR-RP-R2-12-015), Oxford Collaboration for Leadership in Applied Health Research and Care, and Omron Healthcare UK

    Gaussian Processes for Personalized e-Health Monitoring With Wearable Sensors

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    Early warning score adjusted for age to predict the composite outcome of mortality, cardiac arrest or unplanned intensive care unit admission using observational vital-sign data: a multicentre development and validation

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    Objectives Early warning scores (EWS) alerting for in-hospital deterioration are commonly developed using routinely collected vital-sign data from the whole in-hospital population. As these in-hospital populations are dominated by those over the age of 45 years, resultant scores may perform less well in younger age groups. We developed and validated an age-specific early warning score (ASEWS) derived from statistical distributions of vital signs. Design Observational cohort study. Setting Oxford University Hospitals (OUH) July 2013 to March 2018 and Portsmouth Hospitals (PH) NHS Trust January 2010 to March 2017 within the Hospital Alerting Via Electronic Noticeboard database. Participants Hospitalised patients with electronically documented vital-sign observations Outcome Composite outcome of unplanned intensive care unit admission, mortality and cardiac arrest. Methods and results Statistical distributions of vital signs were used to develop an ASEWS to predict the composite outcome within 24 hours. The OUH development set consisted of 2 538 099 vital-sign observation sets from 142 806 admissions (mean age (SD): 59.8 (20.3)). We compared the performance of ASEWS to the National Early Warning Score (NEWS) and our previous EWS (MCEWS) on an OUH validation set consisting of 581 571 observation sets from 25 407 emergency admissions (mean age (SD): 63.0 (21.4)) and a PH validation set consisting of 5 865 997 observation sets from 233 632 emergency admissions (mean age (SD): 64.3 (21.1)). ASEWS performed better in the 16–45 years age group in the OUH validation set (AUROC 0.820 (95% CI 0.815 to 0.824)) and PH validation set (AUROC 0.840 (95% CI 0.839 to 0.841)) than NEWS (AUROC 0.763 (95% CI 0.758 to 0.768) and AUROC 0.836 (95% CI 0.835 to 0.838) respectively) and MCEWS (AUROC 0.808 (95% CI 0.803 to 0.812) and AUROC 0.833 (95% CI 0.831 to 0.834) respectively). Differences in performance were not consistent in the elder age group. Conclusions Accounting for age-related vital sign changes can more accurately detect deterioration in younger patients.</p
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