2019

最新文章

• DEVELOPMENT OF A COMMON PATIENT ASSESSMENT SCALE ACROSS THE CONTINUUM OF CARE: A NESTED MULTIPLE IMPUTATION APPROACH AI翻译
  作者：Gu, Chenyang; Gutman, Roee
  作者单位：Harvard University; Brown University; Harvard University; Harvard Medical School
  摘要：Evaluating and tracking patients' functional status through the post-acute care continuum requires a common instrument. However, different post-acute service providers such as nursing homes, inpatient rehabilitation facilities and home health agencies rely on different instruments to evaluate patients' functional status. These instruments assess similar functional status domains, but they comprise different activities, rating scales and scoring instructions. These differences hinder the compar...
• IDENTIFYING AND ESTIMATING PRINCIPAL CAUSAL EFFECTS IN A MULTI-SITE TRIAL OF EARLY COLLEGE HIGH SCHOOLS AI翻译
  作者：Yuan, Lo-Hua; Feller, Avi; Miratrix, Luke W.
  作者单位：Airbnb; University of California System; University of California Berkeley; Harvard University
  摘要：Randomized trials are often conducted with separate randomizations across multiple sites such as schools, voting districts, or hospitals. These sites can differ in important ways, including the site's implementation quality, local conditions, and the composition of individuals. An important question in practice is whether-and under what assumptions-researchers can leverage this cross-site variation to learn more about the intervention. We address these questions in the principal stratification...
• FRECHET ESTIMATION OF TIME-VARYING COVARIANCE MATRICES FROM SPARSE DATA, WITH APPLICATION TO THE REGIONAL CO-EVOLUTION OF MYELINATION IN THE DEVELOPING BRAIN AI翻译
  作者：Petersen, Alexander; Deoni, Sean; Mueller, Hans-Georg
  作者单位：University of California System; University of California Santa Cruz; Brown University; University of California System; University of California Davis
  摘要：Assessing brain development for small infants is important for determining how the human brain grows during the early period of life when the rate of brain growth is at its peak. The development of MRI techniques has enabled the quantification of brain development. A key quantity that can be extracted from MRI measurements is the level of myelination, where myelin acts as an insulator around nerve fibers and its deployment makes nerve pulse propagation more efficient. The co-variation of myeli...
• JOINT MEAN AND COVARIANCE MODELING OF MULTIPLE HEALTH OUTCOME MEASURES AI翻译
  作者：Niu, Xiaoyue; Hoff, Peter D.
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Duke University
  摘要：Health exams determine a patient's health status by comparing the patient's measurement with a population reference range, a 95% interval derived from a homogeneous reference population. Similarly, most of the established relation among health problems are assumed to hold for the entire population. We use data from the 2009-2010 National Health and Nutrition Examination Survey (NHANES) on four major health problems in the U.S. and apply a joint mean and covariance model to study how the refere...
• ESTIMATING THE RATE CONSTANT FROM BIOSENSOR DATA VIA AN ADAPTIVE VARIATIONAL BAYESIAN APPROACH AI翻译
  作者：Zhang, Ye; Yao, Zhigang; Forssen, Patrik; Fornstedt, Torgny
  作者单位：Technische Universitat Chemnitz; National University of Singapore; Karlstad University
  摘要：The means to obtain the rate constants of a chemical reaction is a fundamental open problem in both science and the industry. Traditional techniques for finding rate constants require either chemical modifications of the reactants or indirect measurements. The rate constant map method is a modern technique to study binding equilibrium and kinetics in chemical reactions. Finding a rate constant map from biosensor data is an ill-posed inverse problem that is usually solved by regularization. In ...
• DISTRIBUTIONAL REGRESSION FORESTS FOR PROBABILISTIC PRECIPITATION FORECASTING IN COMPLEX TERRAIN AI翻译
  作者：Schlosser, Lisa; Hothorn, Torsten; Stauffer, Reto; Zeileis, Achim
  作者单位：University of Innsbruck; Swiss School of Public Health (SSPH+); University of Zurich
  摘要：To obtain a probabilistic model for a dependent variable based on some set of explanatory variables, a distributional approach is often adopted where the parameters of the distribution are linked to regressors. In many classical models this only captures the location of the distribution but over the last decade there has been increasing interest in distributional regression approaches modeling all parameters including location, scale and shape. Notably, so-called nonhomogeneous Gaussian regres...
• LEARNING ALGORITHMS TO EVALUATE FORENSIC GLASS EVIDENCE AI翻译
  作者：Park, Soyoung; Carriquiry, Alicia
  作者单位：Iowa State University; Iowa State University
  摘要：Glass fragments are often compared in the course of a forensic evaluation using their chemical composition determined with technologies such as LA-ICP-MS. At present forensic scientists advocate the use of two comparison criteria based on univariate intervals around all mean elemental concentrations for fragments originating from a known piece of broken glass. The main drawback of this approach is that it does not consider the dependencies between concentrations. Further, when the elemental co...
• COMMON AND INDIVIDUAL STRUCTURE OF BRAIN NETWORKS AI翻译
  作者：Wang, Lu; Zhang, Zhengwu; Dunson, David
  作者单位：Central South University; University of Rochester; Duke University
  摘要：This article focuses on the problem of studying shared-and individual-specific structure in replicated networks or graph-valued data. In particular, the observed data consist of n graphs, G(i), i = 1,..., n, with each graph consisting of a collection of edges between V nodes. In brain connectomics, the graph for an individual corresponds to a set of interconnections among brain regions. Such data can be organized as a V x V binary adjacency matrix A(i) for each i, with ones indicating an edge ...
• GRAPHICAL MODELS FOR ZERO-INFLATED SINGLE CELL GENE EXPRESSION AI翻译
  作者：McDavid, Andrew; Gottardo, Raphael; Simon, Noah; Drton, Mathias
  作者单位：University of Rochester; University of Washington; University of Washington Seattle; Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; University of Copenhagen
  摘要：Bulk gene expression experiments relied on aggregations of thousands of cells to measure the average expression in an organism. Advances in microfluidic and droplet sequencing now permit expression profiling in single cells. This study of cell-to-cell variation reveals that individual cells lack detectable expression of transcripts that appear abundant on a population level, giving rise to zero-inflated expression patterns. To infer gene coregulatory networks from such data, we propose a multi...
• PREDICTION MODELS FOR NETWORK-LINKED DATA AI翻译
  作者：Li, Tianxi; Levina, Elizaveta; Zhu, Ji
  作者单位：University of Virginia; University of Michigan System; University of Michigan
  摘要：Prediction algorithms typically assume the training data are independent samples, but in many modern applications samples come from individuals connected by a network. For example, in adolescent health studies of risktaking behaviors, information on the subjects' social network is often available and plays an important role through network cohesion, the empirically observed phenomenon of friends behaving similarly. Taking cohesion into account in prediction models should allow us to improve th...