Search results for "infer"
showing 10 items of 1371 documents
Prevalence and characteristics of antidepressant drug prescriptions in older Italian patients.
2012
ABSTRACTBackground: During last few decades, the proportion of elderly persons prescribed with antidepressants for the treatment of depression and anxiety has increased. The aim of this study was to evaluate prevalence of antidepressant prescription and related factors in elderly in-patients, as well as the consistency between prescription of antidepressants and specific diagnoses requiring these medications.Methods: Thirty-four internal medicine and four geriatric wards in Italy participated in the Registro Politerapie SIMI–REPOSI study during 2008. In all, 1,155 in-patients, 65 years or older, were enrolled. Prevalence of the use of antidepressants was calculated at both admission and dis…
Association between clusters of diseases and polypharmacy in hospitalized elderly patients: results from the REPOSI study.
2011
BACKGROUND: Although the association between multimorbidity and polypharmacy has been clearly documented, no study has analyzed whether or not specific combinations of diseases influence the prescription of polypharmacy in older persons. We assessed which clusters of diseases are associated with polypharmacy in acute-care elderly in-patients. METHODS: This cross-sectional study was held in 38 Italian internal medicine and geriatric wards participating in the Registro Politerapie SIMI (REPOSI) study during 2008. The study sample included 1155 in-patients aged 65 years or older. Clusters of diseases, defined as two or more co-occurring specific chronic diseases, were identified using the odds…
Performance of PSI, CURB-65, and SCAP scores in predicting the outcome of patients with community-acquired and healthcare-associated pneumonia
2011
The objective was to compare three score systems, pneumonia severity index (PSI), the Confusion-Urea-Respiratory Rate-Blood pressure-65 (CURB-65), and severe community-acquired pneumonia (SCAP), for prediction of the outcomes in a cohort of patients with community-acquired (CAP) and healthcare-associated pneumonia (HCAP). Large multi-center, prospective, observational study was conducted in 55 hospitals. HCAP patients were included in the high classes of CURB-65, PSI and SCAP scores have a mortality rate higher than that of CAP patients. HCAP patients included in the low class of the three severity rules have a significantly higher incidence of adverse events, including development of septi…
X!TandemPipeline: a tool to manage sequence redundancy for protein inference and phosphosite identification
2017
X!TandemPipeline is a software designed to perform protein inference and to manage redundancy in the results of phosphosite identification by database search. It provides the minimal list of proteins or phosphosites that are present in a set of samples using grouping algorithms based on the principle of parsimony. Regarding proteins, a two-level classification is performed, where groups gather proteins sharing at least one peptide and subgroups gather proteins that are not distinguishable according to the identified peptides. Regarding phosphosites, an innovative approach based on the concept of phosphoisland is used to gather overlapping phosphopeptides. The graphical interface of X!Tandem…
How challenging RADseq data turned out to favor coalescent-based species tree inference. A case study in Aichryson (Crassulaceae)
2022
Analysing multiple genomic regions while incorporating detection and qualification of discordance among regions has become standard for understanding phylogenetic relationships. In plants, which usually have comparatively large genomes, this is feasible by the combination of reduced-representation library (RRL) methods and high-throughput sequencing enabling the cost effective acquisition of genomic data for thousands of loci from hundreds of samples. One popular RRL method is RADseq. A major disadvantage of established RADseq approaches is the rather short fragment and sequencing range, leading to loci of little individual phylogenetic information. This issue hampers the application of coa…
Model‐based approaches to unconstrained ordination
2014
Summary Unconstrained ordination is commonly used in ecology to visualize multivariate data, in particular, to visualize the main trends between different sites in terms of their species composition or relative abundance. Methods of unconstrained ordination currently used, such as non-metric multidimensional scaling, are algorithm-based techniques developed and implemented without directly accommodating the statistical properties of the data at hand. Failure to account for these key data properties can lead to misleading results. A model-based approach to unconstrained ordination can address this issue, and in this study, two types of models for ordination are proposed based on finite mixtu…
Calibrating Expert Assessments Using Hierarchical Gaussian Process Models
2020
Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…
Discard ban: A simulation-based approach combining hierarchical Bayesian and food web spatial models
2020
12 pages, 6 figures, 6 tables, 2 appendixes, supplementary data https://doi.org/10.1016/j.marpol.2019.103703
Thompson Sampling Based Active Learning in Probabilistic Programs with Application to Travel Time Estimation
2019
The pertinent problem of Traveling Time Estimation (TTE) is to estimate the travel time, given a start location and a destination, solely based on the coordinates of the points under consideration. This is typically solved by fitting a function based on a sequence of observations. However, it can be expensive or slow to obtain labeled data or measurements to calibrate the estimation function. Active Learning tries to alleviate this problem by actively selecting samples that minimize the total number of samples needed to do accurate inference. Probabilistic Programming Languages (PPL) give us the opportunities to apply powerful Bayesian inference to model problems that involve uncertainties.…
Predicting marine species distributions: complementarity of food-web and Bayesian hierarchical modelling approaches
2019
16 pages, 9 figures, 3 tables, 1 appendix