ライフサイエンスコーパス: statistic

1 eased the prognostic discrimination index (C-statistic).

2 urbulence and its relation to the turbulence statistic.

3 edicts human classifications than any single statistic.

4 done to examine heterogeneity using the I(2) statistic.

5 der the null hypothesis given the sufficient statistic.

6 red using the Area Under the ROC Curve (AUC) statistic.

7 lt appropriateness was assessed by the kappa statistic.

8 valuated by internal 5-fold cross-validation statistics.

9 cs of IC and non-IC adults using descriptive statistics.

10 lection-related parameter alpha from summary statistics.

11 onse classifications with Krippendorff alpha statistics.

12 voxelwise analysis with tract-based spatial statistics.

13 cross space in accordance with natural scene statistics.

14 nimals and tools that shared comparable gist statistics.

15 uated by the Q test in conjunction with I(2) statistics.

16 nd Results database was queried for survival statistics.

17 he responses of other RGCs and natural image statistics.

18 expectations independently of local stimulus statistics.

19 choice predict sufficiently different clonal statistics.

20 upational doses were described using summary statistics.

21 s with the onset of both RSB and Levy flight statistics.

22 alization and informative scores and summary statistics.

23 ted genomic loci not captured by established statistics.

24 ere summarized using nonweighted descriptive statistics.

25 ng bifactor models based on global model fit statistics.

26 significantly higher level according to the statistics.

27 rion level was assessed by using Cohen kappa statistics.

28 cuits, and for the analysis of natural image statistics.

29 ing information were shown using descriptive statistics.

30 dictive results compared with simple summary statistics.

31 under asymptotic conditions, the same clonal statistics.

32 l, or "hotspot," somatic mutation enrichment statistics.

33 Study of Ageing linked with Hospital Episode Statistics.

34 ulation runs in order to build up sufficient statistics.

35 rom CoMM, CoMM-S2 requires only GWAS summary statistics.

36 evaluated by Cox regression and Kaplan-Meier statistics.

37 ence to the "true" RBF and estimated various statistics.

38 nformation through a network as well as node statistics.

39 survival (OS) from relapse and Kaplan-Meier statistics.

40 semble of single vesicles providing detailed statistics.

41 uantitatively by a pathologist share similar statistics.

42 e alteration of reaction rates using quantum statistics.

43 .73, 95%CI 0.72-0.74, p < 0.001) and CABG (C-statistic 0.70, 95%CI 0.68-0.73, p < 0.001), but a poor

44 ients who underwent colectomy/proctectomy (C-statistic 0.73, 95%CI 0.72-0.74, p < 0.001) and CABG (C-

45 and higher out-of-pocket medication costs (c-statistic 0.74).

46 statistic with addition of size variables (C-statistic 0.750 GEP alone, 0.830 GEP with AJCC [P = 0.01

47 f 1 SD 0.43, 95% CI 0.23 to 0.80, p=0.008, C-statistic 0.76).

48 tality accurately in all patients over 65 (c-statistic 0.80).

49 a multivariable logistic regression model (C-statistic 0.82 vs 0.78; p = 0.0009).

50 er adding cardiac troponins in women (DeltaC-statistic = 0.003; likelihood ratio chi-square = 73; p <

51 r adding natriuretic peptides in men (DeltaC-statistic = 0.006; likelihood ratio chi-square = 146; p

52 and Sepsis-3 improved the discrimination (C-statistic = 0.742 +/- 0.005, p < 0.001) of mortality.

53 erived from the coefficients was moderate (C statistic = 0.76).

54 istic = 0.84, 95% CI 0.81-0.86) or sepsis (C-statistic = 0.80, 95% CI 0.78-0.82).

55 s demonstrated the highest discrimination (C statistic = 0.82; 1.5% died if no danger signs, 10% if 1

56 een those who died and those who survived (C statistic = 0.84), but the predictive capacity of the PE

57 atients with specific cirrhosis diagnoses (C-statistic = 0.84, 95% CI 0.81-0.86) or sepsis (C-statist

58 redictor of mortality in the total cohort (C-statistic, 0.71, 95% CI 0.70-0.71, p < 0.001) and for pa

59 te respiratory distress syndrome patients (C-statistic, 0.78; 95% CI, 0.72-0.84).

60 ighest when the observed CNS was included (C statistic, 0.82 [95% CI, 0.81-0.82]), moderate with esti

61 eapplied at a later course in the disease (C-statistic, 0.82; 95% CI, 0.64-0.95).

62 not significantly improve prognostication (c-statistic, 0.89 and 0.90; P = 0.12 for difference), rega

63 g individuals with a bilirubin <2.0 mg/dL (C-statistic, 0.90; 95% CI, 0.82-0.96) and when the score w

64 bly good fit for the model (likelihood-ratio statistic: 2.81, P = 0.094), providing an accurate predi

65 ehavioural responses adjusted to match these statistics, a process that required cortical activity an

66 ferential privacy (DP) while sharing summary statistics about genomic data.

67 ACCOST (Altered Chromatin COnformation STatistics) accomplishes this goal by extending the stat

68 90 m segments on highways relative to median statistics across the entire sampling domain.

69 by population as well as visualization of LD statistics allows the user to easily trace geographic al

70 visiting probabilities, that is, first-order statistics, also play a role in determining the relation

71 In contrast, interactions based on contact statistics among folded globular protein structures repr

72 Tract-based spatial statistics analysis showed significantly increased axial

73 ill depend heavily on the choice of the test statistic and on the underlying genetic architecture of

74 d study quality were assessed using the I(2) statistic and Quality in Prognosis Studies tool, respect

75 HR was used as a summary statistic and was random-effect-models tested.

76 Descriptive statistics and 2 x 2 contingency tables were assessed at

77 Descriptive statistics and a binary logistic regression model were u

78 We generated descriptive statistics and compared pre- and posttreatment uBPA conc

79 Descriptive statistics and generalized estimating equations were per

80 otocol for 10 species and analyzed through F-statistics and Mantel tests.

81 clearly commensurate with the optical image statistics and morphological analysis; and it is driven

82 Using descriptive statistics and multivariate logistic regression, we exam

83 Descriptive statistics and multivariate logistic regressions were us

84 arch Datalink linked to the Hospital Episode Statistics and Office for National Statistics databases.

85 arch Datalink linked to the Hospital Episode Statistics and Office for National Statistics databases.

86 We used chi2 statistics and ordinal regression to assess the signific

87 n be used to integrate, view and browse test statistics and perform genome annotation.

88 y distributions on the nanoscale using image statistics and show that the type of nanospatial distrib

89 cation in dPCR based on multivariate Poisson statistics and suggest reducing the digital occupancy in

90 ng data from city HIV surveillance and vital statistics and the National Death Index.

91 ntermediate experience in bioinformatics and statistics and using R with Bioconductor extensions.

92 y machine-learning algorithms using survival statistics and was compared to conventional algorithms.

93 onsider combinations of conventional summary statistics and/or richer features derived from inferred

94 ity assessment via inter-annotator agreement statistics, and a user-friendly interface convenient for

95 y share their diverse expertise in analysis, statistics, and computation.

96 people; they include research, public health statistics, and eligibility rules for privileges or bene

97 ined descriptive safety and pharmacokinetics statistics, and estimated efficacy results from a longit

98 ompiled from country-based surveys, official statistics, and published studies found through a litera

99 nomy shows that core values from psychology, statistics, and the philosophy of science emerge from a

100 MinION read quality, mapping statistics, and variant calling were computed using an i

101 nt discrimination cue while high-order sound statistics are integrated slowly and contribute substant

102 Extreme events and the related anomalous statistics are ubiquitously observed in many natural sys

103 State-space models with Gaussian statistics are widely used for estimation of such latent

104 cated to visualizing population genetic test statistics at the genomic level is needed.

105 drift and the boundary and construct a test statistic based on finite samples.

106 t the evaluation of the significance of test statistics based on asymptotic theory can be imprecise.

107 ring, correlation analysis, and multivariate statistics can be employed to guide chemical analysis, t

108 These neural ensemble correlation statistics capture high-order sound structure and allow

109 We show that these multiscale statistics clearly differentiate species' architecture a

110 s in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss s

111 Descriptive statistics, correlations, and ANOVA were performed to co

112 effect of high pressure on the nuclear spin statistics could not be directly measured.

113 We collected GWAS summary statistics data for a wide range of human traits and dis

114 The Hospital Episode Statistics database was used to identify adults in Engla

115 l Episode Statistics and Office for National Statistics databases.

116 l Episode Statistics and Office for National Statistics databases.

117 y antireflux surgery in the Hospital Episode Statistics dataset, 811 (3.6%) had surgical reinterventi

118 tifying network architecture with multiscale statistics describing elongation ratios, circularity rat

119 cal loop decomposition to extract a range of statistics describing scale transitions in vein and areo

120 ine learning, we extract detailed behavioral statistics describing the locomotion, pose, biting, and

121 an models were prospectively validated and C-statistics estimated.

122 Data were evaluated using standard statistics, Fisher exact tests, and Wilcoxon rank sum te

123 alized linear mixed effect models, Moran's I statistic for spatial clustering, and Empirical Bayesian

124 The c statistic for this score ranged from 0.84 to 0.88 across

125 endent genome-wide association study summary statistics for ADHD (19,099 cases and 34,194 controls),

126 red t test for continuous endpoints or Kappa statistics for categorical endpoints.

127 uisition time required to collect sufficient statistics for each test is ~ 3 h.

128 We applied mtCOJO to summary statistics for five psychiatric disorders from the Psych

129 Summary statistics for genetic variants strongly associated with

130 erived age and sex stratified CMV prevalence statistics for Germany, Poland, UK, and Chile.

131 Leveraging large-scale summary statistics for migraine (N(cases)/N(controls) = 59,674/3

132 of the approach, identify the most important statistics for parameter estimation, and compare the res

133 Data were analyzed using descriptive statistics for sample characteristics.

134 managed by the Italian National Institute of Statistics for the years 2004-2016.

135 The recently introduced [Formula: see text]-statistics framework predicts distribution functions wit

136 a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst ne

137 t how polygenic risk scores based on summary statistics from a European-based genome-wide association

138 pression quantitative trait loci and summary statistics from a PAH genome-wide association study.Meas

139 formed, it may be challenging to get summary statistics from both exposure-stratified and marginal (i

140 lowing covariate values to these pairs: GWAS statistics from genetically correlated bipolar disorder,

141 assessing heritability models using summary statistics from genome-wide association studies.

142 mechanism for privacy-preserving sharing of statistics from genomic datasets to attain privacy guara

143 Using extensive income-expenditure statistics from India, here we show how a self-consisten

144 ables efficient computation by using summary statistics from standard eQTL analyses.

145 rks from images and in extracting multiscale statistics from subsequent network graph representations

146 sure and in the marginal model using summary statistics from the "joint" model.

147 s of omics data were integrated: (1) summary statistics from the AFGen 2017 GWAS; (2) a whole blood E

148 MS susceptibility as measured using summary statistics from the International Multiple Sclerosis Gen

149 In this study, we used summary statistics from the largest available meta-analyses of g

150 ith the TWAS FUSION method, based on summary statistics from the largest genome-wide association anal

151 e samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC

152 ng simulated data, and show that calculating statistics from tree sequences using this general framew

153 l measures used in these studies are summary statistics from voxelwise measures in the region, withou

154 The spatial scan statistic has been widely used to detect spatial cluster

155 Robust statistics have been widely used in multivariate data an

156 expert-opinion, and 'implementability-score-statistics') identified Six-Actionable Recommendation Th

157 reclassification for MACE prediction, and C-statistic improved from 0.71 to 0.76 (P=0.03).

158 We find entrainment to environmental statistics in both species.

159 Comparative analyses of survival and funding statistics in cancers with high mortality were performed

160 loped a simple framework to estimate summary statistics in each stratum of a binary exposure and in t

161 ed to estimate the null distribution of test statistics in order to achieve the desired false positiv

162 ent an R/Bioconductor package, named struct (Statistics in R using Class-based Templates), which defi

163 We start with summary statistics in the form of SNP effect sizes from a large

164 d hospital admissions data (Hospital Episode Statistics), including adults (>=18 years old) with atop

165 by substituting VA-specific coefficients (C statistic increased from 0.604 to 0.621).

166 As expected, discrimination c-statistics increased only slightly and ranged from 0.73-

167 alysis of data with high heterogeneity (I(2) statistic index > 25%, Cochrane Q statistic p value < 0.

168 -variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically signif

169 ted whether interaural time difference (ITD) statistics inherent in natural acoustic scenes are param

170 ic variants play, by using only GWAS summary statistics instead of individual-level GWAS data.

171 on (old and recent), and the haplotype-based statistic integrated haplotype score to detect more rece

172 The overall significance of the resulting statistic is evaluated using its distribution under the

173 stribution of the classical likelihood-ratio statistic is often intractable when used to test composi

174 The most common form of combining statistics is a sum of SNP-level squared scores, possibl

175 on between weight structure and input/output statistics is fundamental for understanding the computat

176 d from genome-wide association study summary statistics is not yet on a par with APOE e4, a better-es

177 Descriptive statistics, Kaplan-Meier survival curves and Cox proport

178 ts can capture data properties beyond simple statistics, like frequent patterns, spatial changes, out

179 Building and expanding on principles of statistics, machine learning, and scientific inquiry, we

180 ze neuronal activity to form sequences whose statistics match experimental observations.

181 nt and the maximum clustering set-proportion statistic (MCS-P) are used to select appropriate paramet

182 Summary statistics (mean and standard deviation of regional volu

183 stability using physically motivated summary statistics measured in integrations of the first [Formul

184 The current SNP index method and G-statistic method for BSA-Seq data analysis require relat

185 Generalized scan statistics methodology was used to estimate the area und

186 Despite these sobering statistics, most bioinformatics and computational biolog

187 onducted using US National Center for Health Statistics natality files for the years 2011-2017.

188 discovery rate <0.25; normalized enrichment statistic [NES], 2.15).

189 uminance variations, but also at the rate of statistics not available from luminance information alon

190 By integrating RNA-seq data and GWAS summary statistics, novel computational methods allow unbiased i

191 including the screening test result had a C-statistic of 0.860, c-slope of 0.997, and R(2) of 0.597.

192 emonstrated a random effects meta-analysis C-statistic of 0.88 (95% CI, 0.82-0.93) for incident TB.

193 External validation generated a C-statistic of 75.0% (95% CI, 73.2% to 76.7%).

194 t equations, and both combined resulted in C statistics of 0.61 (95% CI, 0.60 to 0.62), 0.76 (95% CI,

195 el cut-off <=2 points (all P < 0.001) with c-statistics of 0.680, 0.695, and 0.681, respectively.

196 randomization (GSMR) analysis using summary statistics of a genome-wide association study meta-analy

197 ompute and compare allele frequencies and LD statistics of dbSNP catalogued variants.

198 ws us to formulate precise links between the statistics of environmental challenges and the ants' col

199 ramework to implement many currently defined statistics of genome sequence (making the statistics' re

200 ects that alter both the spectrum and photon statistics of HHG, thus departing from all previous appr

201 ons of chromosome territories, and the shape statistics of individual chromosomes.

202 ely efficient DNN surrogate, we revealed the statistics of model responses, providing a detailed pict

203 work, we have initially discussed the global statistics of neurological disorders reported by WHO and

204 ts, in which both the first and second-order statistics of observations dynamically evolve over time.

205 int analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of geneticall

206 ere, existing knowledge about structures and statistics of our environment is referred to as prior, w

207 likelihood via simulation either use summary statistics of the data or are at risk of producing subst

208 ration at atomic resolution by examining the statistics of the energy changes that occur when the loc

209 g of intracellular diffusivity through local statistics of the instantaneous displacements of freely

210 dicted by gender associations encoded in the statistics of the language they speak.

211 lso disclose queen toots and quacks, showing statistics of the occurrence of queen pipes over the ent

212 tegy depends both on the noise level and the statistics of the signals.

213 diffusion coefficient(3-10) and non-Gaussian statistics of the tracer displacements(6,9,10).

214 omparing internal five-fold cross-validation statistics of the training data.

215 plicit), as well as the corresponding branch statistics of tree shape.

216 ors replicated these findings in the summary statistics of two major published GWASs for anxiety, and

217 ale meta-analysis of our results and summary statistics of two recent insomnia GWAS and 13 significan

218 Jointly, these statistics offer a unique signature to distinguish oppor

219 annot be applied to either GWAS/eQTL summary statistics or cases with more than two possibly correlat

220 Derived from the theory of order statistics, our method controls the false discovery rate

221 rom physician claims, hospitalization, vital statistics, outpatient prescription, kidney, and HIV dat

222 eity (I(2) statistic index > 25%, Cochrane Q statistic p value < 0.05), random-effects model was used

223 ng new features such as query searches and a statistics page, and enabled direct link-outs to chemica

224 Estimation of the univariate statistic parameters and genotype plus genotype x enviro

225 of the tools required for understanding the statistics, physics, and dynamics of drought and its cau

226 he world, we make inferences by learning the statistics present in the sensory environment.

227 This statistic reduces to the log-linear growth rate for data

228 al constraints, the ideal optimally uses the statistics relating local intensity patterns in moving i

229 enome assemblies are commonly assessed using statistics relating to contiguity of the assembly.

230 ed statistics of genome sequence (making the statistics' relationship to the underlying genealogical

231 rmined by using the DeLong test and Youden J statistic, respectively.

232 emerge because of a failure to learn sensory statistics, resulting in an impaired representation of t

233 The C-statistics results for prediction of prolonged length of

234 Bayesian statistics revealed no interaction between predictabilit

235 f mortality was summarized using descriptive statistics; secondary outcome was, risks for mortality.

236 The S-CVI statistic showed the content validity of the scale (S-CV

237 Multivariate statistics showed that flavonoids characterizing PS were

238 Voxelwise statistics showed that the diffusion abnormalities for b

239 sholds for each cluster using data-dependent statistics, specifically standard deviation and mean.

240 les our approach to also evaluate other test statistics such as SKATs, higher criticism approaches, a

241 We compare individual and global statistics, such as a newly introduced length-weighted a

242 rception showed correlation with natural ITD statistics, supporting our hypothesis.

243 Descriptive statistics, t-tests, one-way analysis of variance, and P

244 ues for the SWME method also had greater DOA statistics than that for the OAME method over relatively

245 l recurrence rates ratio (ERRR), a smoothing statistic that is gradually gaining currency in modeling

246 learning is a branch of computer science and statistics that generates predictive or descriptive mode

247 n the potential of combining genetic summary statistics that represent the mutational burden in genes

248 the UK population by using a haplotype-based statistic, the trait singleton density score (tSDS), dri

249 MPORTANCE According to 2017 U.S. agriculture statistics, the combined value of production and sales f

250 Besides standard linear burden-type statistics, this enables our approach to also evaluate o

251 (ITDv) were combined in a Fisher information statistic to assess the amount of azimuthal information

252 was performed using the Fleiss kappa (kappa) statistic to determine consistency among raters.

253 We applied Kaplan-Meier statistics to assess unadjusted survival.

254 ow adjusting pupil dynamics to environmental statistics to augment information transmission.

255 Sharing data with CDC death records and OPO statistics to characterize underlying process and system

256 e auditory system might encode these summary statistics to create internal representations of these s

257 hen applied to current U.S. cancer incidence statistics to estimate the number of new patients each y

258 In this paper, we use [Formula: see text]-statistics to formulate a statistical approach for epide

259 We implemented spatial statistics to identify global-local hotspots and regress

260 In this study, we apply three spatial statistics to locations of CD68+ macrophages within huma

261 ior to randomization; and appropriate use of statistics to monitor studies and analyse their results.

262 in state-trace analysis make use of Bayesian statistics to quantify the evidence for and against a di

263 t linear Ricker growth models using Bayesian statistics to seven time series of elk population survey

264 nd SARS-CoV-2 transmission and extreme value statistics to show that the distribution of secondary ca

265 Applying circular statistics to test for changes in year-round flowering,

266 We subsequently apply multiple spatial statistics to the analysis of eight different mosaics in

267 ross longitudinal time points, network-based statistics unraveled progressive network degeneration or

268 cially those that enable exploration of test statistics using auxiliary information (covariates) to w

269 Kappa statistic was 0.74 (95% CI; 0.58 to 0.89); 0.64 and 0.79

270 y heterogeneity between trials, and the I(2) statistic was calculated to estimate variation across st

271 The kappa statistic was used to compare ratings between examiners.

272 ndividuals that included these three summary statistics was used as final outcome.

273 Next, with current data submission statistics, we demonstrate that the proteomics field is

274 ity data from the National Center for Health Statistics, we employed demographic techniques to pursue

275 e full use of widely available GWASs summary statistics, we extend TisCoMM to use summary-level data,

276 Using full atom counting statistics, we find the lowest resonance to consist of c

277 lution topography, image analysis and crater statistics, we have dated 35 different surfaces in Kasei

278 ncepts of probability theory and inferential statistics, we present a comprehensive theoretical appro

279 tcomes, VIA image agreement rates, and Kappa statistic were compared before, during, and after traini

280 udent t test, logistic regression, and kappa statistics were applied.

281 C statistics were calculated for AI-ECG AF model output, C

282 Summary descriptive statistics were calculated.

283 Allele statistics were cataloged for each genomic position that

284 mals and tools would remain, when image gist statistics were comparable across categories.

285 sensitivity, specificity, and kappa (kappa) statistics were generated for each diagnosis.

286 outcome data were collected and descriptive statistics were performed on variables of interest.

287 Descriptive statistics were used to summarize baseline patient chara

288 Descriptive statistics were used to summarize mutation and copy numb

289 specificity (95% CI, inconsistency I-square statistic) were 0.74 (0.70-0.77, 71.5%) and 0.88 (0.86-0

290 icism approaches, and maximum-single-variant-statistics, where asymptotic theory might be involved or

291 eral computations thus reflect natural input statistics, whereas central brain activity precisely cod

292 as reflects unsupervised learning of stimuli statistics, whereas choice bias results from supervised

293 essed with clinical parameters using routine statistics, while the diagnostic capacity of individual

294 by GEP class, as shown by increase in the C-statistic with addition of size variables (C-statistic 0

295 demonstrate that combining multiple spatial statistics with a maximum likelihood approach better pre

296 andard descriptive analyses included summary statistics with percentages and means.

297 amples of up to 2 cm(2) , pairing multiscale statistics with traits representing axes of resource tra

298 Our analysis shows that k-gram statistics with visibility graph motifs produce fast and

299 was assessed using Harrell's concordance (c)-statistic, with a value of 0.70 or higher considered to

300 Q_Young Person versions have goodness-of-fit statistics within the interval 0.5, 1.5 and person separ