ライフサイエンスコーパス: data source

1 ional models based on single gene expression data sources".

2 information is needed from a single uniform data source.

3 seline method, which used only one phenotype data source.

4 years and older) from the years 2000-11 as a data source.

5 available published literature provided the data source.

6 urrent studies are limited to using a single data source.

7 nce over sequence-based models regardless of data source.

8 al Health Insurance Research Database as its data source.

9 ogy using cheminformatics approaches and big data sources.

10 Injury deaths were estimated from additional data sources.

11 ent publications will be used as the primary data sources.

12 elated data types from a variety of original data sources.

13 We construct individual DEGs on two data sources.

14 d analyzing sets of genes from heterogeneous data sources.

15 and random errors associated with different data sources.

16 nking together 17 different individual-level data sources.

17 ic biases associated with different types of data sources.

18 ared meaning across heterogeneous biomedical data sources.

19 n England recorded in four electronic health data sources.

20 ly be conflicting measurements from multiple data sources.

21 uded in the statistical model using multiple data sources.

22 C-related genes, and human TFs from multiple data sources.

23 accine safety evaluations using claims-based data sources.

24 2 cardiovascular presentations in any of the data sources.

25 mpendium of annotated diseases mined from 68 data sources.

26 I prediction models by prioritizing multiple data sources.

27 coefficients assessed agreement between the data sources.

28 ference from emission estimates based on EPA data sources.

29 ow allows for evaluation of patient-oriented data sources.

30 association between gene sets and empirical data sources.

31 ates gene-specific information from multiple data sources.

32 rated genome-wide data from a broad range of data sources.

33 tainment in stroke registries using external data sources.

34 ve team using two research methods and three data sources.

35 st match the structure of specific empirical data sources.

36 inear time trends, and representativeness of data sources.

37 the dependence and the heterogeneity of the data sources.

38 etermine a single 'joint' clustering for all data sources.

39 test proteins that were represented in all 3 data sources.

40 mproved by constraining the model with omics data sources.

41 were compared with nationally representative data sources.

42 y utilize the potential of these multi-omics data sources.

43 ke it easily adaptable to other diseases and data sources.

44 eases, it is necessary to integrate multiple data sources.

45 tor, and outcome, potentially from different data sources.

46 hms from relatively short-term or unreliable data sources.

47 to the difference in scope, assumptions, and data sources.

48 nical data, claims data, or a hybrid of both data sources.

49 using six governmental and intergovernmental data sources.

50 derived from mobile phones and other dynamic data sources.

51 ictive cell models is the lack of integrated data sources.

52 Data Sources: A PubMed search through November 10, 2015,

53 Data Sources: A search strategy consisting of gray liter

54 Data Sources: A systematic review was performed by searc

55 Data Sources: A systematic review, an environmental scan

56 on the Internet to meet the specific online data source acquisition needs of e-health researchers.

57 rvival rates varied minimally with augmented data sources, although using external death data without

58 ing spatial and temporal resolutions of each data source and generate inference about dynamics on sca

59 wrong-site surgery in US settings varied by data source and procedure (median estimate, 0.09 events

60 methodology exploits the information in each data source and produces accurate weekly ILI predictions

61 were initially conducted separately for each data source and time point to examine generalizability o

62 Moreover, ORegAnno assembles these disparate data sources and annotations into a single, high quality

63 eractions; parallel or sequential processes; data sources and computational tools at different stages

64 dults, which is based on extensive published data sources and considers specific drugs and resistance

65 ave the velocity, volume, and variety of big data sources and contain additional geographic informati

66 Substance and Compound databases, including data sources and contents, data organization, data submi

67 factorization (iONMF) to integrate multiple data sources and discover non-overlapping, class-specifi

68 m one data set are less predictive for other data sources and highlight the importance of bias correc

69 In sub-Saharan Africa, robust routine data sources and historical epidemiological observations

70 Since then, a variety of new data sources and improvements in functionality have cont

71 the urgent need for integrating non-Western data sources and intensifying cooperation to more effect

72 diovascular (CV) pairs that appeared in both data sources and investigated whether our approach can d

73 Data Sources and MEDLINE and Embase (1956 to May 2017) w

74 ithin the limitations of currently available data sources and methodologies, these findings suggest t

75 rs intending to work with data from multiple data sources and provides a platform for ongoing data in

76 DATA SOURCES AND REVIEW Scoping review methodology follo

77 Data Sources and Study Selection: Systematic search of E

78 Several digital data sources and systems have been advanced for use in a

79 er care was evaluated using population-based data sources and was defined as direct transport from th

80 higher-order emissions, integrate additional data sources and/or user-defined functions into multiple

81 l-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of t

82 ve framework combining disparate methods and data sources, and assessed subnational pandemic potentia

83 nderreporting of both IPV and TOP in primary data sources, and inherent difficulties in validation.

84 ransdisciplinary and systems approaches, new data sources, and stakeholder partnerships.

85 We assessed both primary data sources, and the 2013 Global Burden of Disease Stud

86 any annotated genome curated in the Ensembl data sources, and to integrate local mapping data.

87 denoting the same biomedical concepts across data sources, and using declaratively represented forwar

88 The two major data sources are electronic health records from traditio

89 Distributed networks of health-care data sources are increasingly being utilized to conduct

90 urred prior to the satellite era, thus other data sources are required to better understand long-term

91 target population, taken from administrative data sources, are considered analogous to overlapping "c

92 tomation with flexibility to incorporate new data sources as needed.

93 Next, we provide an overview of data sources available for wealth research.

94 Data Sources: Based on PRISMA guidelines, a librarian-le

95 Teeth are an important data source because they are generally well preserved in

96 empowerment indicator from widely available data sources, broadening opportunities for monitoring an

97 s and to test whether an external electronic data source can improve reporting.

98 efforts are exploring ways in which multiple data sources can be integrated to generate a more compre

99 gnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the e

100 These data sources can be temporally limited, spatially aggreg

101 Independent data sources can be used to augment post-marketing drug

102 ligned within and between species and across data sources can be used to inform studies of genome evo

103 generated inventory found that the selected data sources can provide information with equal or bette

104 asurements to more globally continuous PM2.5 data sources can yield valuable improvements to PM2.5 ch

105 g the same statistical methodology with each data source, classification of hospital outlier status a

106 Data Sources: Clinical trials, observational analyses, r

107 Data sources comprised relevant UK policy documents and

108 The data source consisted of 311 individuals who had psychos

109 Data sources consisted of governmental data, data from n

110 All linked data sources contained longitudinal information covering

111 ed and combined with other information, this data source could be useful for monitoring disease trend

112 DATA SOURCES, DATA SELECTION, AND DATA EXTRACTION: Searc

113 DATA SOURCE: Data were obtained from a PubMed search of

114 s a web resource that consolidates disparate data sources describing drug-gene interactions and gene

115 estimates, as a result of methodological and data source differences.

116 We investigate multiple potential data sources (e.g., satellite column and surface estimat

117 rn or switchgrass), treatment of coproducts, data sources, end of life assumptions, and displaced fos

118 data source with an empirically acquired IMS data source, establishing an algorithm-accessible link b

119 ological considerations regarding the use of data sources, exposure and outcome definitions, timing o

120 ble deceased donors in the US and could be a data source for CMS to implement new OPO performance met

121 The data source for FCOIs was Open Payments, which is public

122 Controversy remains as to the most favorable data source for measuring postoperative complications fo

123 rmance than expected was assessed using each data source for superficial surgical site infection (SSI

124 ased on virtual models constitute a valuable data source for testing hypotheses about craniodental fo

125 sample is the largest and most comprehensive data source for the combined study of genetic and enviro

126 We examine a freely available, open data source for this use: access logs from the online en

127 es enabling cross-platform comparisons among data sources for analysis.

128 ll available demographic and epidemiological data sources for China at the provincial level.

129 Challenges with alternative data sources for disease surveillance include differenti

130 Data sources for model parameters included National Heal

131 are increasingly receiving attention as new data sources for phenotype prediction.

132 e the strengths and limitations of different data sources for pregnancy-related research in patients

133 AS) of chronic periodontitis (CP) offer rich data sources for the investigation of candidate genes, f

134 49 years) from 257 population-representative data sources from 107 countries worldwide.

135 We collated 134 population-representative data sources from 83 countries with measured serum retin

136 The experimental data sources from a nested case-control study cohort, co

137 We identified scabies epidemiological data sources from an extensive literature search and hos

138 and through the contribution of unpublished data sources from collaborators, an updated version of m

139 e an overview of selected ideas, models, and data sources from decision research that can fuel new li

140 isks of VTE by using several recently linked data sources from England.

141 Using several data sources from populations of European descent, inclu

142 and variety of publically available gene set data sources has been increased, and its advanced search

143 gies that leverage the use of Internet-based data sources have been proposed as a way to complement d

144 As the two data sources have complementary strengths-high veracity

145 n recent years, social and real-time digital data sources have provided new means of studying disease

146 Data sources identified 1,216 outcomes of CRC surgery th

147 Data sources identified 2,990 outcomes, which were used

148 nationally representative surveys, and other data sources identified through a systematic review, web

149 We show that the integration of multiple data sources improves the predictive accuracy of retriev

150 or biochemical data, few integrate these two data sources in a unified fashion.

151 We discuss the potential of new data sources in accounting for seasonal population movem

152 lts demonstrate the value of newly available data sources in addressing long-standing scientific ques

153 volume prescribers (LVPs) based on available data sources in New York State.

154 or vertically (separate measures within each data source) in order to preserve patient privacy.

155 Data sources include PubMed, Embase, the Cochrane Centra

156 Data sources included interviews (n = 22), walk-throughs

157 Data sources included MEDLINE, EMBASE, Cochrane Database

158 Data sources included PubMed for trials and investigatio

159 Data sources included searches of electronic databases (

160 Data sources included the National Vital Statistics Syst

161 Data sources included the Surveillance, Epidemiology, an

162 The data sources included varied by pathogen and included sy

163 g of multi-read allocation with a variety of data sources including histone ChIP-seq.

164 y in the US by leveraging data from multiple data sources including: Google searches, Twitter microbl

165 We triangulated among several data sources, including 19 semi-structured interviews wi

166 e by utilizing a wider variety of models and data sources, including global food trade data, processi

167 We searched multiple data sources, including Ovid MEDLINE, Cochrane, and Emba

168 Data sources, including PubMed and conference proceeding

169 Combining different task contrasts or data sources increased prediction accuracies in some but

170 tions outperform every prediction using each data source independently, (2) our methodology can produ

171 iverse long-tail data convert numerous small data sources into big data for improved knowledge about

172 tegrating metabolomics data with other omics data sources into genome-scale models of metabolism have

173 estimates, generated independently with each data source, into a single prediction of ILI utilizing m

174 r (AUD) using a reliable, valid, and uniform data source is needed.

175 The data source is the French health insurance database.

176 ons across cancer types based on integrative data sources is still a pressing need.

177 Data Sources: Learning environment interventions were id

178 riation and proteomics data from large scale data sources (LSS).

179 Used together, linked data sources may allow clinicians, researchers, and pati

180 rior as well as the ease with which parallel data sources may be utilized without increasing the mode

181 icrobiology data suggest that using external data sources may improve the accuracy of AE reporting.

182 Nonrandomized data sources may inform the initial design of ATSs, whic

183 Data Sources: Medical databases (ie, Medline, EMBASE, an

184 edistricting was evaluated with two distinct data sources, Medicare claims and the University HealthS

185 DATA SOURCES MEDLINE, EMBASE, Cumulative Index to Nursin

186 e treatment of AKs relative to other methods.DATA SOURCES MEDLINE, EMBASE,Web of Knowledge, and Cochr

187 Data sources (Medline, Embase, Maternity and Infant care

188 Data Sources: MEDLINE and EMBASE (without language restr

189 Data Sources: MEDLINE, Cochrane Library, CINAHL, and Int

190 Data Sources: MEDLINE, Cochrane Library, EMBASE, and tri

191 Data Sources: MEDLINE, EMBASE, and Cochrane Central Regi

192 Data Sources: MEDLINE, EMBASE, and Web of Science (1995

193 Data Sources: MEDLINE, EMBASE, CINAHL, and Cochrane CENT

194 Data Sources: MEDLINE, EMBASE, Web of Science, CENTRAL,

195 Data Sources: MEDLINE, PubMed, Cumulative Index for Nurs

196 Data Sources: MEDLINE; Cochrane Central Register of Cont

197 weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.

198 Data Sources: Multiple databases from 1947 to October 20

199 Data Sources: Multiple electronic databases from January

200 However, most current studies used only one data source of human disease phenotype.

201 Using a rich data source of rubella incidence, we show that patterns

202 ic strategy for combining multiple different data sources of human disease phenotype and predicting d

203 Longitudinal data sources offer new opportunities for the evaluation

204 insight into these interactions, individual data sources often provide only partial information rega

205 hically resolved household survey and census data sources on child deaths to produce estimates of und

206 Agreement between the data sources on hospital outlier status classification w

207 s will be linked to eight different national data sources on mortality, school records, residential h

208 tly determine a separate clustering for each data source or determine a single 'joint' clustering for

209 horizontally (separate patients within each data source) or vertically (separate measures within eac

210 Data Sources: Ovid MEDLINE (from 1946), Cochrane Central

211 Data Sources: Ovid MEDLINE, CINAHL, and the Cochrane Lib

212 obal Vision Database with recently published data sources permitted modelling of cause of vision loss

213 ve as benchmarks; 4) optimize the use of new data sources, platforms, and natural experiments; and 5)

214 Combining data sources presents a systematic approach to study mol

215 Three independent data sources provide evidence that R cannot be much abov

216 rated by recent studies, these heterogeneous data sources provide the opportunity to gain insights in

217 computational model and HTS data from a big data source (PubChem) were used to profile environmental

218 DATA SOURCES: Publications in human subjects were identi

219 Data Sources: Publications in MEDLINE and CINAHL between

220 Data Sources: Published literature and expert opinion.

221 Data Sources: PubMed search of phase 1 cancer drug trial

222 Data Sources: Pubmed, CINAHL, and Web of Science (Januar

223 amework synthesized evidence from a range of data sources relating to influenza transmission and vacc

224 ew introduces a range of "omics" and patient data sources relevant to managing infections and propose

225 um" knowledge discovery across heterogeneous data sources remains a major challenge.

226 rmore, integration of knowledge from various data sources remains a monumental challenge that has to

227 ze-up since the 1990s, using two independent data sources (satellite telemetry data and passive acous

228 Data Sources: Searches of 4 bibliographic databases, wit

229 Data Sources: Searches were conducted in PubMed and refe

230 cted information about study aim and design, data source, selected population, outcome definition, pa

231 Data Sources: Several electronic databases from inceptio

232 Additionally when the data sources (strains) are not identified (e.g. in datas

233 DATA SOURCES, STUDY SELECTION, AND DATA SYNTHESIS: An In

234 DATA SOURCES, STUDY SELECTION, AND DATA SYNTHESIS: Data

235 Data Sources, Study Selection, and Data Synthesis: PubMe

236 DATA SOURCES, STUDY SELECTION, AND DATA SYNTHESIS: We se

237 models rely on human interactions, multiple data sources such as clinical surveillance and Internet

238 Yet, there are many third-party data sources, such as immunofluorescence microscopy or p

239 Digital data sources, such as medical claims, mobile phone call

240 model, the HIV Synthesis Model, to multiple data sources (surveillance data provided by Public Healt

241 Mouse Brain Atlas as the curated anatomical data source that is linked to MALDI-based IMS experiment

242 grative analysis of multiple high-throughput data sources that are available for a common sample set

243 ate intraspecific variation, review existing data sources that could help parameterize models that ac

244 f the following methodological elements: the data source, the inclusion and exclusion criteria, the s

245 in Australia by using multiple, independent data sources.The study was designed to compare relevant

246 Data Sources: The Cochrane Central Register of Controlle

247 Price increases for SSBs in two distinct data sources, their timing, and the patterns of change i

248 Using these data sources, this article traces the historical generat

249 arch for and access a range of human genomic data sources through a single, easy-to-use interface, fr

250 job title-based exposure data from a public data source to construct a job exposure matrix and test

251 rden of Disease Study 2013 and several other data sources to assess the economic burden of symptomati

252 in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellula

253 cost-effectiveness of utilizing existing big data sources to conduct population health studies.

254 r machine system, to integrate heterogeneous data sources to considerably improve on the quantity and

255 We used secondary data sources to correct for out-migration.

256 ata from structured interviews and secondary data sources to determine lifetime residence, which was

257 We used 3 publicly available government data sources to estimate anti-HCV prevalence in each US

258 We utilized multiple publicly available data sources to evaluate the association between introdu

259 sequences and genome information from public data sources to form a knowledge base.

260 -based prospective designs rely on secondary data sources to identify PD cases.

261 he potential of geolocalized studies of open data sources to improve current analysis and develop ind

262 cal frameworks jointly model these different data sources to reveal an accurate, holistic view of the

263 sing existing models and relevant supporting data sources to track chemicals during production, proce

264 hen describe three studies drawing from "big data" sources to assess liberal-conservative differences

265 Using these different data sources together may improve our understanding of g

266 cioeconomic scenarios as well as in physical data sources (topography and climate model).

267 Data Sources: Two independent reviewers selected studies

268 ease (CHD) prevalence using population-based data sources up to year 2010.

269 s of photosynthetic activity are the primary data source used to study changes in global vegetation p

270 review we provide an overview of the various data sources used to construct gene sets and the statist

271 predictive abilities of three different omic data sources using eight representative methods for six

272 Analyses were based on the following data sources (using most recent sources that provided ap

273 e prospective addresses contained in these 2 data sources was good (85%), it was diminished among bla

274 A comprehensive search of the following data sources was performed without language restriction

275 Across 2 large data sources, we found decreases in intake and purchases

276 Conclusions: Using existing nontraditional data sources, we have developed a Web-based platform for

277 Data Sources: We performed a systematic literature searc

278 Data Sources: We searched PubMed, EMBASE, The Cochrane L

279 mong different varieties and among different data sources were considerable.

280 Data sources were FDA approval packages and databases (J

281 ion that drug-SE pairs that appeared in both data sources were highly enriched with true signals, man

282 Data sources were identified by using PubMed in 2016.

283 In this systematic analysis, data sources were identified from GBD 2013 for the preva

284 Data sources were participants, parents, teachers, infor

285 Data sources were PubMed, Cochrane Library, and EMBASE d

286 Several data sources were searched from inception to September 2

287 differences in patient survival rates across data sources were small (</=1 percentage point), OPTN on

288 Several data sources were used to include a broad, comprehensive

289 Further data sources were: websites, grey literature, research i

290 Furthermore, our results suggest that data sources which allow for spatial averaging will prom

291 of subcellular protein distribution are new data sources which have attracted much attention in rece

292 y integrating a number of publicly available data sources, which have subsequently been used to build

293 heterogeneity present in the different omics data sources, which makes it difficult to discern the co

294 mation from traditional surveillance and big data sources, which seems the most promising option movi

295 epidemiologic approaches are combined, these data sources will be constrained by their intrinsic limi

296 need by (1) integrating a curated anatomical data source with an empirically acquired IMS data source

297 l topics can be measured, as they all have a data source with defined numerators and denominators.

298 rch and hospital insurance data and analysed data sources with a Bayesian meta-regression modelling t

299 metrics are generally scattered in different data sources with various levels of aggregation hamperin

300 hat is general enough to accommodate diverse data sources, yet rigorous enough to provide a strong me