ライフサイエンスコーパス: data-driven

1 Biomedical research is becoming increasingly data driven.

2 t approaches: deep-sequence, model-based and data-driven.

3 were incorporated into algorithms to support data-driven adjustments of resuscitation with therapeuti

4 we report an accurate and broadly applicable data-driven algorithm for dimensionality reduction.

5 Methods: We propose a data-driven algorithm, centroid of distribution (COD), t

6 propose a motion correction framework with a data-driven algorithm, that is, using the PET raw data i

7 generate new health care disparities through data-driven, algorithm-based biomedical research and cli

8 To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentificat

9 sities for research mice: filling the gap in data-driven alternatives.

10 Genomes (KEGG)-defined pathways and 2 novel data-driven analyses were conducted to consider differen

11 aches, and the challenges in embracing fully data-driven analyses.

12 dvances in multiregion recording techniques, data-driven analysis approaches, and machine-learning-ba

13 the presumption of a binary classification, data-driven analysis identified 4 subgroups of depressio

14 Data-driven analysis led to the selection of 30 potentia

15 h the human sleep cycle, we used a Markovian data-driven analysis of continuous neuroimaging data fro

16 We performed data-driven analysis of the interactions between the ext

17 Together, findings from the present data-driven analysis suggest that intrinsic communicatio

18 computational data pre-processing tools and data-driven analysis techniques based on Monte Carlo per

19 In this large-scale retrospective data-driven analysis, we examined global trends in vacci

20 nostics using all metabolomics features with data-driven analysis.

21 The data-driven analytical method identified distinct cell t

22 However, current approaches are entirely data driven and agnostic to evolutionary theory.

23 and practical utilization of these should be data driven and evolve based on both experience and data

24 The algorithms are purely data-driven and can be used for other detection tasks in

25 e results, testing the effect of losartan on data-driven and contextual processing of traumatic mater

26 The AI system combines data-driven and domain-expertise methodologies, includin

27 versity in biomedical research have not been data-driven and increase the risk of translational failu

28 It encompasses both data-driven and theory-driven efforts.

29 Our approach will help close the gap between data-driven and theory-driven models of neural dynamics.

30 Our data driven approach takes into account not only a broad

31 A multivariate data-driven approach (partial least squares) was used to

32 individual variability using a multivariate data-driven approach (principal component analysis) on a

33 ing approach performed similarly well to the data-driven approach and both outperformed classical lin

34 In this paper, we propose a data-driven approach assisted by deep neural networks (D

35 We present a new data-driven approach based on a combination of tree ring

36 rcome this limitation, we developed a hybrid data-driven approach based on combined neural networks (

37 Here, we propose a data-driven approach based on deep neural networks to di

38 A data-driven approach based on Hidden Markov modeling all

39 We here propose an alternative data-driven approach based on PARAFAC tensor decompositi

40 In contrast, we adopted a data-driven approach by using machine learning (Support

41 Our data-driven approach could facilitate healthcare systems

42 n mode decomposition can offer a model-free, data-driven approach for analyzing and forecasting traff

43 We introduce a new data-driven approach for grouping together transcripts i

44 This data-driven approach for identifying symptom-specific ta

45 We present a data-driven approach for modeling a grating meta-structu

46 Here we introduce a data-driven approach in which artificial neural networks

47 Our multimodal data-driven approach is a useful way to detangle the int

48 Our data-driven approach may constitute a generalizable solu

49 We discuss how such a data-driven approach might be used generally to generate

50 Our data-driven approach predicts the stability of natural a

51 Our data-driven approach reveals the structure and complexit

52 Here we show a data-driven approach that reliably produces one-month-ah

53 The network thus offers a new data-driven approach to automatically derive ratings of

54 We conclude that a personalised, data-driven approach to care with active management from

55 clinical data sets may provide a meaningful data-driven approach to categorize patients for populati

56 sionality reduction hypothesis by relating a data-driven approach to characterizing the complexity of

57 We believe applying a similar data-driven approach to clinical polytrauma may help to

58 To address this, we used a high-dimensional, data-driven approach to devise a framework for parsing h

59 Here, we report a data-driven approach to elucidate degradation trends of

60 "Ring Breaker" uses a data-driven approach to enable the prediction of ring-fo

61 We use a data-driven approach to estimate in vivo k (cat)s using

62 with Adversarial variational autoencoder), a data-driven approach to fulfill the task of dimensionali

63 In conclusion, NN(C-part) is a valid data-driven approach to provide GPP and RECO estimates a

64 It adopts a data-driven approach to select predictive regions as wel

65 These findings highlight the utility of a data-driven approach to select putative toxins and sugge

66 We use a data-driven approach to study the magnetic and thermodyn

67 Here we present a novel and data-driven approach to understand and characterize the

68 A data-driven approach was used to model these reactions b

69 By incorporating the data-driven approach, we can determine that risk factors

70 patterns, demonstrating the potential of our data-driven approach.

71 e gaps in risk assessment of OMPs requires a data-driven approach.

72 Here we demonstrate how data-driven approaches can vastly accelerate the search

73 robiology researchers to (semi)-unsupervised data-driven approaches for inferring latent structures t

74 ts in knowledge, and the role of large-scale data-driven approaches in future progress and discovery.

75 on, this new construct enables us to explore data-driven approaches in RNA research.

76 We reviewed studies that leveraged data-driven approaches to examining heterogeneity in Alz

77 sions, and demonstrate the efficacy of using data-driven approaches to study the representation of th

78 lites originated in microbes is critical for data-driven approaches to understand how microbial metab

79 f the state of the science of digital health data-driven approaches to understanding human behavior.

80 ntify depression subtypes using clinical and data-driven approaches, examine differences in genetic a

81 With unbiased data-driven approaches, we predicted that Egr1, a transc

82 ting in increasing importance of integrative data-driven approaches.

83 A probabilistic data-driven archetype analysis approach applied in a lar

84 Our study provides proof of concept that data-driven, automated, operator-independent IZ sampling

85 On a data-driven basis, the proposed deep generative model ca

86 It is data-driven because all parameters can be derived from H

87 and large-scale experimental surveys into a data-driven, biologically realistic simulation of the aw

88 for OCT representations for unbiased, purely data-driven biomarker discovery.

89 between the chronological brain age and the 'data-driven' brain age using functional MRI (fMRI) and d

90 Data-driven building classification achieves high sensit

91 and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted c

92 However, more formal, data-driven, causal mechanisms of long-term groundwater

93 mall set of empirical studies devoted to the data-driven characterization of behavioral changes induc

94 Research using data-driven cluster analysis has proposed five subgroups

95 er grid-cells, whose size was determined via data-driven clustering of the fixation points.

96 Using these proteins for data-driven clustering, we identified three robust patho

97 The proposed data-driven clusters differ in diabetes progression and

98 ns of object representations, we developed a data-driven computational model of similarity judgements

99 Hence, we propose a novel, data-driven concept of an integrated cell, iCell.

100 ualitative and quantitative findings using a data driven convergent synthesis approach.

101 rtex (S1) of the awake mouse, we optimized a data-driven cortical state classifier to predict single-

102 PAREameters inferred criteria and that using data-driven criteria enables the identification of addit

103 s for the COVID-19 era, and will necessitate data-driven decision making, political will and commitme

104 een theory-driven cognitive neuroscience and data-driven decoding approaches, there is a need for met

105 In sum, a data-driven decoding of brain states reveals the distinc

106 The Koopman operator-based, data-driven decomposition technique gives insight into s

107 elevation in risk represents a potential new data-driven definition of septic shock.

108 ate the potential of SR for accelerating the data-driven design and discovery of new materials with i

109 ork (cGAN) methodology that allows reliable, data-driven determination of involuntary subject motion

110 computation has been studied intensively, a data-driven determination of this precision remains a fu

111 f electrical performance and even generating data-driven device-specific models.

112 tial resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatm

113 tions between specific cancer types and both data-driven dietary patterns determined by empirical ana

114 on, cell types, disease architecture or even data driven discoveries.

115 ons to guide researchers towards meaningful, data-driven discoveries in the science of emotion and be

116 We conclude that a data-driven discovery approach is sufficient to discover

117 cs in laboratory mice (Mus musculus) enables data-driven discovery of biological network components a

118 Here we introduce data-driven discretization, a method for learning optimi

119 d with computational advances-has catapulted data-driven efforts forward.

120 We review recent data-driven efforts that shed light into the origin and

121 Here, we summarize emerging data-driven efforts to delineate more homogeneous ASD su

122 ing modern machine learning methods to build data-driven emulators.

123 Furthermore, our data-driven enrichment analysis showed that CYP2D6 is si

124 TM oceanic DIC inventory, we provide a fully data-driven estimate of the PETM carbon source.

125 Here, we provide new data-driven estimates of cropland-N(2) O emissions acros

126 dynamics and allows us to closely reproduce data-driven estimates of net C exports through the river

127 and Evaluation (IHME), produces influential, data-driven estimates of the burden of disease and prema

128 we describe an analysis method that provides data-driven estimates of these effects in task-based fMR

129 r detection has been developed by means of a data-driven estimation of the degrees of freedom and sca

130 The rapid, data-driven evolution of these procedures is unique and

131 ns, and fine feature reconstruction; provide data-driven experimental design guidelines; and provide

132 r high-performing combinations, we propose a data-driven experimental design.

133 Here, we present decRiPPter (Data-driven Exploratory Class-independent RiPP TrackER),

134 e arbitrary, high-dimensional functions in a data-driven fashion.

135 a fine level of granularity, determined in a data-driven fashion.

136 ctional data analysis of histograms provided data driven features (FPC1,2,3) used in further model bu

137 0.653 by combining both knowledge-driven and data-driven features, based on the one-year claims histo

138 potentially related to COPD readmission, and data-driven features, which are extracted from the patie

139 We further develop a data-driven framework for identifying combinatorial sign

140 cial intelligence (AI) approaches to build a data-driven framework that integrates several data sourc

141 Here, we develop a data-driven framework to identify resource-user typologi

142 Here, we describe an unsupervised, data-driven framework to perform hypothesis testing in s

143 l lines from 30 cancer types and developed a data-driven framework to prioritize candidates for cance

144 The development of novel data-driven functional analytic tools has enabled the de

145 Data-driven functional characterization revealed associa

146 reconstructions were performed and compared: data-driven gating (DDG) (we use the term DDG-retro to d

147 Data-driven gating (DDG) using signals derived from PET

148 This previously described algorithm uses data-driven gene list weightings to produce a comprehens

149 functional connectivity was quantified via a data-driven global brain connectivity method and compare

150 This brief report provides a data-driven global snapshot of expert-perceived impacts

151 An automated data-driven GPM detection technique tracking the center

152 The ML component is an imaging data-driven graph-based semi-supervised learning model a

153 acy when considering transitions between the data-driven grid units (using a fine granularity, and ab

154 archical clustering was used to identify new data-driven groups of participants; differences on socia

155 indings open the possibility of studying new data-driven groups that represent children with NDDs mor

156 rn statistical learning methods to develop a data-driven health measure based on 21 years of pharmacy

157 of the principal challenges associated with data-driven heterogeneity analyses and outline avenues f

158 re extracted using treelet transformation, a data-driven hierarchical clustering and dimension reduct

159 s) lightly anesthetized marmosets and used a data-driven hierarchical clustering approach to derive s

160 Furthermore, the reduction in data-driven human mobility metrics showed correlation wi

161 Hence, it is a highly useful approach for data-driven hypothesis generation from disparate clinica

162 expression analysis is a valuable asset for data-driven hypothesis generation.

163 pository and private data, GsmPlot can spark data-driven ideas and hence promote the epigenetic resea

164 ically heterogeneous, could benefit from the data-driven identification of disease subtypes.

165 ng with advanced registration techniques and data-driven image fusion.

166 ssful translation will require that we 1) be data-driven in our selection of species for study; 2) us

167 d as an alternative to capture such effects, data-driven inference of their parameters is not well-es

168 unity-wide efforts to organize multi-source, data-driven information related to cell type taxonomies

169 The website provides data-driven information to help individuals and policy m

170 These data-driven information-based models have been found to

171 We illustrate our view with a data-driven, information theoretic analysis of a dataset

172 We examined the association of data-driven integrated care assisted by information and

173 ein activity states allowed an effective and data-driven integration of the prior knowledge by InferA

174 and dimensional disorder models with a fully data-driven intrinsic network-level analysis (intrinsic

175 We used a data-driven machine learning method for GWAS to uncover

176 from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phe

177 It is unclear whether data-driven machine learning models, which are trained o

178 sical process models with the versatility of data-driven machine learning.

179 unting for potential collinearity, we used a data-driven machine-learning approach.

180 While data-driven machine-learning approaches learn rules to m

181 l terminus, groups together transcripts in a data-driven manner allowing transcript-level analysis wh

182 randomization were applied in a large-scale, data-driven manner to explore genetic correlations and c

183 s predict how sequence maps to function in a data-driven manner without requiring a detailed model of

184 ferent brain regions in individual mice in a data-driven manner, while taking into account mouse-spec

185 ques for studying disease heterogeneity in a data-driven manner.

186 more likely to be observed experimentally in data-driven manner.

187 This application of toric theory enables a data-driven mapping of covariance relationships in singl

188 We then develop a series of data-driven Markov models that isolate and identify the

189 A data-driven method for respiratory gating in PET has rec

190 Data-driven methodologies facilitate the discovery of "h

191 a subtype has been reported in studies using data-driven methodologies.

192 In this paper, we apply a data-driven methodology based on shareability networks t

193 Over time, data-driven methods and member feedback should be used t

194 edia data seems to be robust when supervised data-driven methods are used.

195 Novel data-driven methods at the metabolite and network levels

196 de a systematic evaluation of word-level and data-driven methods for text analysis for generating wel

197 Data-driven methods provided robust estimates, approxima

198 Implementing data-driven methods that use real-time collection and an

199 We used data-driven methods to define wheezing phenotypes in pre

200 lected from an integrated approach using (1) data-driven methods, including Support Vector Machine wi

201 t our method improves largely over competing data-driven methods.

202 ta analysis that can combine traditional and data-driven methods.

203 We integrate both stylized and mobile phone data-driven mobility patterns in an agent-based transmis

204 We propose an inverse design tool based on a data-driven model for unit cells' temporal responses.

205 We use a data-driven model of household demography to estimate th

206 Here we develop a data-driven model of the within-host dynamics of extende

207 iting mutually-exclusive sub-categories, the data-driven model repositions semantics, language, socia

208 were extracted (per sleep state) to train a data-driven model that estimates brain-age, with the mos

209 n addition to joint kinematics, the proposed data-driven model-based approach also estimated several

210 rize these networks, we used systems-focused data-driven modeling approaches to identify cross-tissue

211 This data-driven modeling framework substantially improves ou

212 st three years postnatally were submitted to data-driven modeling to differentiate ASD outcomes.

213 Through a data-driven modelling approach using probabilistic dimen

214 These results show that data-driven modelling based on spatial datasets and mode

215 We used a data-driven modelling framework applied to infection dat

216 ing amounts of data, the knowledge of robust data-driven modelling methods professed within the QSAR

217 These data-driven models are trained to predict a subspace wit

218 In neuroscience, data-driven models of neural circuits that span multiple

219 ting, instead, that the predictions of these data-driven models should be used to guide model buildin

220 Data-driven modularity-based parcellation of the rat med

221 Data-driven motion can be estimated using image registra

222 Conclusion: The proposed COD-based data-driven motion correction method outperformed FIR an

223 everal case studies are presented, including data-driven motion estimation and correction for brain s

224 Applications such as data-driven motion estimation, which require many short

225 an be used for various applications, such as data-driven motion estimation, whole-body surveys, quick

226 Conclusion: A fully automated data-driven motion-compensation approach was established

227 We sought to construct a data-driven multi-dimensional typology of medication non

228 Here, using a data-driven, multimodal approach for studying brain stru

229 dPCR instruments can be exploited to perform data-driven multiplexing in a single fluorescent channel

230 racting more information from data to enable data-driven multiplexing with high accuracy.

231 A data-driven multivariate analysis integrating all outcom

232 This database provides a public resource for data-driven nanoinformatics modeling research aimed at r

233 Our findings suggest that data-driven network-based methods can identify patients

234 med alternative neural scores computed using data-driven neuroimaging methods, including multivariate

235 Data-driven neuroimaging studies frequently report a neg

236 emonstrate the potential of such mechanistic data-driven neuron models, we created a simulation envir

237 It then examines some of the data-driven "next-generation" approaches that are needed

238 vercome these limitations, here we develop a data-driven non-parametric framework to estimate the tol

239 rediction of complex traits, which assumes a data-driven nonparametric prior for cis-eQTL effect size

240 In this article, we propose a data-driven, nonparametric approach that allows complex

241 esting that the optimal network structure is data-driven, not sample size driven.

242 Here, we propose a data-driven, objective and systematic method for derivin

243 nsive workflow to address these issues using data-driven offset stacking, wavelet-crosscorrelation fi

244 ion lacks coherence as a construct, and that data-driven ontologies lay the groundwork for a cumulati

245 f finding progressible hits were overcome by data-driven optimization.

246 We used a novel, whole-brain, data-driven parcellation technique-non-negative matrix f

247 We use data-driven partial least squares regression to identify

248 e goal of providing doctors and patients the data-driven personalized decision recommendations.

249 -based estimates of ecosystem T permitting a data-driven perspective on the role of plants' water use

250 The hardness model is then combined with the data-driven phase diagram generation tool to expand the

251 policy tool to identify gaps in care, inform data-driven policy decisions, set benchmarks for quality

252 kage provides the novel utility to integrate data-driven primary transcript annotations with transcri

253 -based software application that is built on data-driven principles for configuring and customizing d

254 Given the noisy nature of data-driven prior knowledge, which potentially contains

255 We designed and tested two data-driven procedures for subtype diagnosis: the first

256 A data-driven process distilled a gene list from peer-revi

257 Data-driven processing was measured by the level of blur

258 The in vitro bioassay data-driven profiling strategy developed in this study m

259 We applied a data-driven proteomics approach, measuring serum levels

260 rate an approach that can be used to support data-driven quality improvements.

261 We build a data-driven quantitative model, simulations of which rec

262 -19 treatment trials now in order to develop data-driven recommendations regarding the risks and bene

263 We address this need with our Data-Driven Reference (DDR) approach, which employs stab

264 formed by using a bayesian network to reveal data-driven relationships between eNose volatile organic

265 The past two decades have seen data-driven repurposing characterized by signature-based

266 Data-driven research in biomedical science requires stru

267 ection and analysis, which is critical for a data-driven response to this public health challenge.

268 h advances will enable scientifically based, data-driven risk assessments that inform decisions invol

269 , and 17 healthy controls were included in a data-driven scaled subprofile model (SSM)/principal-comp

270 We sought to determine whether a data-driven scheduling approach improves Operative Suite

271 Experimental laboratory management and data-driven science require centralized software for sha

272 Avant-garde uses a novel data-driven scoring strategy: signals are refined by lea

273 he intestine and provide a framework for the data-driven selection of excipients.

274 Data-driven, single-cell computational modeling revealed

275 In ORSO, users interact within a data-driven social network, where they can favorite data

276 In an increasingly data-driven society, a new generation of cutting-edge te

277 ique labeled dataset for further feature and data-driven soft-sensor development.

278 t on individual and combined datasets using (data-driven) soft independent modelling of class analogi

279 Here we have developed a generalizable, data-driven solution to this challenge using eco-acousti

280 We conclude that data-driven spectroscopic brain examination supports tha

281 We developed a simple, data-driven spike detection method using a scaled form o

282 Additionally, many data-driven strategies employ computational modelling an

283 Next, we discuss the promise of using data-driven strategies to discover novel subtypes of dep

284 In particular, data-driven studies have led to new discoveries of previ

285 ip extraction from literature and facilitate data-driven studies of how microbial metabolism contribu

286 The results of this data-driven study showed that highly accurate and genera

287 A data-driven synthesis planning program is one component

288 Using a data-driven systems biology approach, we built a MB-spec

289 Here we use a data-driven systems biology meta-analytical approach acr

290 A data-driven task PLS analysis also showed greater co-act

291 ing the ontologies were expert consultation, data-driven techniques and reuse of terms from existing

292 g individuals within the family level, and a data-driven temporal network for human movements motivat

293 Data-driven theories on the role of these streams during

294 s combination of unsupervised and supervised data-driven tools provides a framework that could be use

295 es-specific biomass objective functions in a data-driven, unbiased fashion.

296 a toxicological framework and (2) provide a data-driven, unsupervised grouping of genes impacted by

297 ing GMMs, estimating cluster properties in a data-driven way.

298 We carried out a data-driven, whole-brain volumetric analysis on regional

299 Here we present a holistic, data-driven workflow for deriving statistical models of

300 In today's data-driven world, the ability to process large data vol