ライフサイエンスコーパス: random sampling

1 amine in China through multi-stage clustered random sampling.

2 which households were selected by stratified random sampling.

3 habitats relative to the null hypothesis of random sampling.

4 es of active shRNAs up to 5-fold relative to random sampling.

5 ded into two groups: index and validation by random sampling.

6 or both k-fold cross-validation and repeated random sampling.

7 s provide other useful functionalities, e.g. random sampling.

8 lected from birth certificates by stratified random sampling.

9 enumeration area were selected using simple random sampling.

10 g 422 patient charts selected through simple random sampling.

11 tudy was conducted by multi-stage stratified random sampling.

12 om 2016 participants, selected by stratified random sampling.

13 lts older than age 18 years were included by random sampling.

14 s were selected via purposive and stratified random sampling.

15 nt from July to August 2022 using systematic random sampling.

16 to non-epidemiological factors, such as non-random sampling.

17 e performance as a dataset constructed using random sampling.

18 inverse probability weighting for stratified random sampling.

19 ) inmates using the proportionate stratified random sampling.

20 stimators-within the framework of stratified random sampling.

21 l survey employing nationally-representative random sampling.

22 ced data, the model uses on-the-fly weighted random sampling.

23 age siblings of survivors selected by simple random sampling.

24 ins City, Brazil, were identified by cluster random sampling.

25 t low-angle shot sequence is used with quasi-random sampling.

26 be consistently obtained by using localized random sampling.

27 te resampling, different-site resampling and random sampling.

28 g and regulating facilities using stratified random sampling.

29 e using ImageJ to perform systematic uniform random sampling.

30 to 3.5-fold greater than that expected from random sampling.

31 s (VDCs) from each district were selected by random sampling.

32 selected from the district using multi stage random sampling.

33 Eligible samples were selected using cluster random sampling.

34 es sampling had a small efficiency gain over random sampling (10% and 12% decrease on average over al

35 ation spectroscopic-filtering with iterative random sampling (2D-COS-firs) is reported.

36 Using cluster random sampling, 351 COPD patients participated in and c

37 study was carried out recalculating % RVT by random sampling 50%, 33%, and 25% of TB slides per speci

38 We used stratified random sampling (according to age, residence [urban vs r

39 We found that compared to random sampling, active learning strongly helps performa

40 cantly better when they were chosen with the random sampling algorithm.

41 iciently measure this quantity, we develop a random sampling algorithm.

42 importance sampling distribution and using a random sampling algorithm; however, selection of importa

43 e significant precision benefits relative to random sampling alone.

44 ns between 2015 and 2017 by using stratified random sampling among study populations.

45 Of the total random sampling analyses, 50% showed a highly statistica

46 We combine random sampling and active machine learning (ML) to opti

47 With methodology based on random sampling and behavioural tests of genuineness, we

48 howed that training set designs outperformed random sampling and earlier methods that either minimize

49 We selected individuals from a census using random sampling and estimated age-sex-standardized hepat

50 ared to competing approaches, including both random sampling and information maximization.

51 fold, namely decreasing genetic diversity by random sampling and leading to population-wide inbreedin

52 trospective cohort study was performed using random sampling and manual review of electronic health r

53 A systematic random sampling and multi-stage sampling method were use

54 atum radiatum were analyzed using systematic random sampling and serial section analyses.

55 sections were sampled by systematic uniform random sampling and stained with Masson trichrome, and t

56 Random sampling and testing of COVID-19 are needed with

57 sed stereology approach that uses systematic-random sampling and thin focal-plane optical sectioning

58 kends), (ii) completely random or stratified random sampling, and (iii) a number of sampling strategi

59 abias were selected using computer-generated random sampling, and 189 087 households were visited.

60 difference covariance matrix with iterative random sampling, and is capable of revealing contaminati

61 We used flux balance analysis, random sampling, and principal component analysis to exp

62 the laying sequence, the selection criteria, random sampling, and the duration and temperature of tra

63 A stratified random sampling approach considering age, sex, BMI, como

64 his lack of large patient data, we present a random sampling approach to generate clinical COVID-19 o

65 Our analysis is based on a random sampling approach using real data sets from 16 pu

66 A stratified random sampling approach was used to enhance precision i

67 Using a stratified random sampling approach, 50,000 individuals were select

68 Compared to the previous random sampling approach, which was capable of sampling

69 We conclude that random sampling artifact is very unlikely to be the expl

70 A random sampling assigned participants into group 1 (with

71 ified two-stage cluster sampling with simple random sampling at each stage for each stratum was used

72 Region (Chile) using multi-stage, stratified random sampling at the commune-block-household levels.

73 . WebTool, a user-friendly online server for random sampling-based evaluation of distance significanc

74 In this article, we present a random-sampling-based statistical algorithm to identify

75 A random-sampling-based susceptible-infected-removed (SIR)

76 ed in the peak gain of the synthesized quasi-random sampling bases from the frequency-diverse cavity.

77 tremuloides) by a factor of 4-7 compared to random sampling because it favoured plants taller than t

78 arated from the training set by a stratified random sampling before the analysis, was used to determi

79 ults and suggest that similar performance to random sampling can be achieved with a fraction of the s

80 lineages, bootstrapping based on stratified random sampling combined with a k-mer-based genome-wide

81 ons following a metabolic perturbation using random sampling, compares the simulated flux distributio

82 use of museum records: first without initial random sampling, comparison with contemporary results ca

83 lding on the strength of what can be a small random sampling component.

84 Subsequently, 42 subjects recruited from a random sampling cross-sectional study were analysed.

85 'almost unbiased' theorem similar to that of random-sampling cross-validation.

86 Our original conclusion that random sampling described a trophic cascade that was wea

87 Random sampling described a trophic cascade, but it was

88 ade, but it was weaker than the one that non-random sampling described.

89 ion in 2001, 2006, and 2011, using a 2-stage random sampling design in 2 urban and 3 rural strata.

90 sis of hospital records, we used a two-stage random sampling design to create a nationally representa

91 We used a multistage random sampling design to generate a representative samp

92 ed when samples are collected using a simple random sampling design.

93 Using a multistage, random-sampling design with replacement, the Monitoring

94 UK was selected by a multi-stage, clustered, random-sampling design.

95 I consider both one-way and two-way random sampling designs, and develop an approach to Baye

96 tion, from either altered labor partition or random sampling, drives the community into distinct stru

97 ssembly mechanisms may explain this pattern, random sampling effects can create this pattern through

98 our computer simulations show that these non-random sampling features may affect the topological info

99 onfidential cannabis survey using stratified random sampling for frequency of past-year cannabis use

100 survey about cannabis use, using stratified random sampling for frequency of past-year use and patie

101 of the AI field, we present RENOIR (REpeated random sampliNg fOr machIne leaRning), a modular open-so

102 erpart of UniCon3D that performs traditional random sampling for protein modeling aided by predicted

103 Random sampling for selecting non-interacting pairs resu

104 lts was collected by mail using a stratified random sampling frame from March to September 2024.

105 rticipants from community health centers and random sampling from 12 southeastern states.

106 Control subjects were selected by stratified random sampling from 28,123 incident pancreatic cancers

107 Random sampling from a cohort of 5,928 subjects was perf

108 re composed for each procedure by stratified random sampling from a list of experts nominated by the

109 o histologic sections selected by systematic random sampling from four mice were immunostained and im

110 Participants were selected using stratified random sampling from general surgery residency programs

111 form a retroviral particle are determined by random sampling from the cell-and thus dictated by the c

112 stically valid conclusions from data involve random sampling from the population.

113 Controls were selected by simple random sampling from the remaining HHCs.

114 study participants were identified by simple random sampling from the state's health department elect

115 In a random sampling from the unenhanced (n = 201) and Defini

116 We show how a tradition of non-random sampling has confounded this understanding in a t

117 s using a global sensitivity approach called Random Sampling High Dimensional Model Representation (R

118 This work presents an adapted Random Sampling - High Dimensional Model Representation

119 al sensitivity analysis (SA) method based on Random Sampling-High Dimensional Model Representation (R

120 The Random Sampling-High Dimensional Model Representation (R

121 ion using the recently developed approach of random sampling-high-dimensional model representation (R

122 This was in contrast to the impact of weekly random sampling (i.e., using saliva swabs) of at least 1

123 t diversity-sampling strategies outperformed random sampling, i.e., no active learning.

124 ations with higher accuracy than traditional random sampling in a small benchmark of 6 proteins; (ii)

125 74 adults who were selected using multistage random sampling in Gondar town, North West, Ethiopia.

126 ground, is significantly more efficient than random sampling in identifying genetic variants associat

127 sidue protein can find its native topomer by random sampling in just approximately 100 ms.

128 sampling in makeshift settlements and simple random sampling in Nayapara registered camp.

129 e greater than those in surveys using simple random sampling in order to obtain similarly precise pre

130 were recruited using multistage cluster-area random sampling in Port-au-Prince, Haiti.

131 s to 1,521 physicians selected by stratified random sampling in the 1995 National Ambulatory Medical

132 y demonstrate efficiently verifiable quantum random sampling in the measurement-based model of quantu

133 he eligible subsets at each node by weighted random sampling instead of simple random sampling, with

134 of the study was divided using proportionate random sampling into the 14 governorates.

135 Its superior performance over random sampling is demonstrated on secondary ion mass sp

136 ighting, aim to enable valid inferences when random sampling is not feasible.

137 hat was weaker than the one described by non-random sampling is unchanged.

138 advanced and able to overcome the under- and random-sampling issues of the current sequencing approac

139 While this is true for random sampling, it is not true with separate sampling,

140 c analysis of kinase pathways, and over 2000 random sampling iterations using the PamGene PamStation

141 RNA sequencing techniques are susceptible to random sampling limitations due to the complexity of the

142 OPEN-Stereo implements the stereological random sampling method for unbiased cell counting.

143 ory of leishmaniasis respectively by cluster random sampling method in a ratio of 1:1.

144 Systematic random sampling method was employed to select the study

145 A stratified, cluster-random sampling method was used to select students acros

146 A stratified cluster random sampling method was used.

147 A systematic random sampling method, based on the university's list,

148 Finally, based on the Monte Carlo random sampling method, the workspace of the robot is co

149 anuary 2020 and December 2022 using a simple random sampling method.

150 20-50 years) were recruited through a simple random sampling method.

151 he research area was determined by a layered random sampling method.

152 care workers who were selected using simple random sampling method.

153 olled from community health centers by using random sampling methods across 12 states in the Southeas

154 e compare the uniformly-random and localized random sampling methods over a large space of sampling p

155 Combining a random sampling model with a terrageny generates numeric

156 compare different methodologies, we picked a random sampling of 100 nasopharyngeal specimens recovere

157 HLAMatchmaker using a linear regression of a random sampling of 1000 HLA alleles.

158 In a random sampling of 130 genes encoding secretory proteins

159 unds in a structure descriptor space so that random sampling of 20% of the whole data set produced an

160 A random sampling of 230 BACs indicated an average insert

161 A random sampling of 2510 segmented images each for the li

162 The algorithm was further evaluated in a random sampling of 3195 CTPA examinations from January 2

163 r library preparation, receptor preparation, random sampling of a library, ligand preparation, molecu

164 ng of "super-emitters" that may be missed by random sampling of a subset of the total.

165 Manual review was performed on a random sampling of AMD cases to optimize accuracy.

166 ed using a methodology based on 100 repeated random sampling of calibration and test sets.

167 d of rare disease alleles substantially over random sampling of cases or controls or sampling based o

168 elop an algorithm for efficiently performing random sampling of causal graphs.

169 Random sampling of cDNAs from two evolutionarily diverge

170 east three orders of magnitude compared to a random sampling of compact folds.

171 Our method is based on random sampling of conformation space and subsequent loc

172 y native-like conformations mostly resort to random sampling of conformations to achieve computationa

173 matic sampling of cases (when necessary) and random sampling of controls will be implemented.

174 ng and gene dropping of genotype vectors and random sampling of each of the model parameters from the

175 rategies, ranging from naive thresholding to random sampling of edges, on mobility data from the U.S.

176 ed from rotamer libraries, are combined with random sampling of explicit urea molecules in interactio

177 ster was lower than would be expected from a random sampling of genomes from this outbreak, but data

178 to account the special nature of these data: random sampling of genomic segments from one or more ind

179 We characterize these biases for random sampling of genotypes as well as samples drawn fr

180 comparable to those reported from a national random sampling of HIV-infected men and women receiving

181 ty in the assignment of genotypes because of random sampling of homologous base pairs in heterozygote

182 of state of Sao Paulo, using systematic and random sampling of households between March 2004 and Jul

183 cal regions of Liberia, followed by a simple random sampling of households.

184 Random sampling of ICU professionals from a directory.

185 Multi-stage stratified random sampling of individuals aged 60 and older, repres

186 onentially more likely to occur upon uniform random sampling of inputs than complex outputs are.

187 Lunar meteorites represent a more random sampling of lunar material than the Apollo or Lun

188 nds, we recommend a size correction based on random sampling of modules when using biological process

189 are (i) potential participation bias despite random sampling of named individuals from the National H

190 Sequencing errors and random sampling of nucleotide types among sequencing rea

191 Overall, random sampling of only one lumen in CVCs causing CRBSI

192 field diversity was consistent with a nearly random sampling of orientation, spatial phase, and retin

193 ifurcation sets, numerical continuation, and random sampling of parameters.

194 also normally distributed, consistent with a random sampling of parental genes.

195 studies (necessary to assess causality), non-random sampling of participants by many studies, and the

196 Stratified random sampling of patients from outpatient clinics was

197 Stability analysis through random sampling of patients or features demonstrated tha

198 ng with leave-one-out cross-validation, with random sampling of single sequences from individuals on

199 The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=58

200 -to-Centiloid conversion equation related to random sampling of the calibration dataset and PET image

201 obability) is no more efficient than uniform random sampling of the entire population, because resour

202 ults to 5 serosurveys (n = 22 118) that used random sampling of the general population.

203 Uniform random sampling of the steady-state flux space allows fo

204 We used k-fold cross validation and random sampling of the SVM classifier to assess the clas

205 e models for molecular design is to navigate random sampling of the vast molecular space, and produce

206 each annotation of a test gene is derived by random sampling of the whole genome.

207 Random sampling of this cohort was performed, with appro

208 n cortical layers 2-6, and are composed of a random sampling of transcriptomic cell types.

209 ers several years after war using consistent random sampling of war-affected people across several We

210 Regularized GGM coupled with iterative random samplings of genes was expanded into a network th

211 Data sets ascertained by random sampling often harbor cryptic relatedness that ca

212 tive set selection substantially outperforms random sampling on the entire SRA set of RNA-seq samples

213 Ne reflects the effect of random sampling on the genetic composition of a populati

214 ge of quantum computation is through quantum random sampling performed on quantum computing devices.

215 ed in the laboratory for some generations by random sampling prior to artificial selection.

216 In the first stage, we used a simple random-sampling procedure stratified by economic-geograp

217 f 250 farmers selected through a multi-stage random sampling process.

218 We expect that the localized random sampling protocol helps to explain the evolutiona

219 imating population variance under stratified random sampling, providing more accurate and reliable es

220 care providers enrolled consecutively by non-random sampling PWH with lab-confirmed COVID-19, diagnos

221 s is applied to mitigate the inadequacies of random sampling, random forest (RF) together with the co

222 theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling,

223 ly selected 150 for the study using a simple random sampling routine in Stata.

224 riented sampling RRT*), DR-RRT* (directional random sampling RRT*), and hybrid-RRT* in three differen

225 nt algorithms for search space size, uniform random sampling, segment placement probabilities, mean,

226 and compares favorably with a conventional, random sampling, semiquantitative method.

227 incide with histone acetylation islands, and random sampling shows that 33% (13/39) of these can func

228 Households were identified using simple random sampling (SRS) in Nayapara and multistage cluster

229 On the basis of random sampling strategies, 44 870 households were eligi

230 elected from municipal rolls using two-stage random sampling stratified by province and municipality

231 ion and validation data sets by using simple random sampling stratified by sex, BMI category, and age

232 We address model fitting for simple random sampling study designs as well as stratified desi

233 ited 100 homeless persons using a stratified random sampling technique from January to March 2014.

234 eneralized extreme value (GEV) models, and a random sampling technique is developed to quantify multi

235 from March 1 to 30, 2020 by using systematic random sampling technique to select study participants a

236 A systematic random sampling technique was used to select 359 study p

237 oss - sectional design study with systematic random sampling technique was used to select 630 adults.

238 A simple random sampling technique was used to select participant

239 A systematic random sampling technique was used to select study parti

240 Systematic random sampling technique was used.

241 ticipants were drawn by a stratified cluster random sampling technique.

242 ticipants were selected using the systematic random sampling technique.

243 Simple random sampling techniques were employed to select healt

244 Simple random sampling techniques were used to select a subset

245 week and had better accuracy than stratified random sampling techniques.

246 tative sites (Chiri, C, and Wabero, W) using random sampling techniques.

247 The method of random sampling that was used was comparable with linear

248 classic survey sampling strategies based on random sampling therefore require increasingly large sam

249 ate that initial primary cell heterogeneity, random sampling, time in culture, and even mild differen

250 eoarthritis Project, using stratified simple random sampling to achieve balance according to radiogra

251 c computing, and probabilistic computing use random sampling to approximate solutions to various prob

252 hone dialing who were selected by stratified random sampling to approximate the age, sex, and county

253 of existing motif-finding tools by employing random sampling to effectively remove non-motif-containi

254 This cross-sectional study used multistage random sampling to enroll 1,134 12-year-old schoolchildr

255 of this organism, we conducted a systematic random sampling to identify 3,000 nasopharyngeal swab sp

256 : This cross-sectional study used stratified random sampling to identify registered clinical trials w

257 al asthma lungs underwent systematic uniform random sampling to obtain 239 lung tissue samples that w

258 ased, observational study, we used two-phase random sampling to recruit adults with disabilities and

259 om 15 February to 15 March 2020 using simple random sampling to recruit study participants among type

260 hybrid of multistage sampling and systematic random sampling to select the respondents.

261 Using repeated random sampling to simulate donor-recipient genotype pai

262 number of sequence combinations makes wholly random sampling unfeasible, two key simplifications may

263 Field surveys and random sampling validated the thematic maps, achieving a

264 As smaller studies are especially subject to random sampling variability, using QR as the outcome int

265 Random sampling was applied to assess the sensitivity an

266 y and May 2023 a cross-sectional survey with random sampling was conducted in the six clinics in an u

267 Simple random sampling was done to select the study participant

268 Random sampling was stratified by frequency of past-year

269 Random sampling was the least biased method.

270 ligible PD, all 234 with POPF were included, random sampling was used on the remainder to select 250

271 Systematic random sampling was used to allocate 10 clusters each to

272 Stratified random sampling was used to ensure that the proportion o

273 Multistage, cluster random sampling was used to select a nationally represen

274 In brief, a multilevel stratified random sampling was used to select representative sample

275 To select samples, simple random sampling was used.

276 Linear programming and uniform random sampling were applied herein to identify candidat

277 in any sampling design, including stratified random sampling, where stratum weights may increase the

278 logical receptive field structure, localized random sampling, which yields significantly improved CS

279 tness variants by up to fivefold compared to random sampling while requiring experimental characteriz

280 onal survey data that were collected through random sampling with a sample size of at least 100 indiv

281 Patients were recruited using systematic random sampling with an interval of 2.

282 Multistage stratified cluster random sampling with probability-proportional-to-size pr

283 mples achieved either through bootstrapping (random sampling with replacement) or subsampling (random

284 Cluster random samplings with probability proportionate to size

285 y weighted random sampling instead of simple random sampling, with the weights tilted in favor of the

286 on carried by each neuron arises purely from random sampling within the stimulus space.

287 m sampling with replacement) or subsampling (random sampling without replacement) on learning data.

288 statistically sufficient to explain TL under random sampling, without the intervention of any biologi