ライフサイエンスコーパス: prediction accuracy

1 oosting (for width), and random forests (for prediction accuracy).

2 sting TEST and ECOSAR tools suggest improved prediction accuracy.

3 es in an effort to improve the cleavage site prediction accuracy.

4 -PFP demonstrated substantial improvement in prediction accuracy.

5 0% ranked restraints can greatly improve the prediction accuracy.

6 hod has the potential to significantly boost prediction accuracy.

7 methods in both computational efficiency and prediction accuracy.

8 ion and validation data sets, providing 100% prediction accuracy.

9 ene Ontology (GO) data dramatically improves prediction accuracy.

10 All methods resulted in almost equal prediction accuracy.

11 fragments are useful features for improving prediction accuracy.

12 ndicating their significant contributions to prediction accuracy.

13 fect sizes across all the markers to improve prediction accuracy.

14 nd binding assay) had significant effects on prediction accuracy.

15 extinction or reconsolidation, depending on prediction accuracy.

16 performed better than others in terms of the prediction accuracy.

17 that a larger number of qubits gives better prediction accuracy.

18 reconstruction with quantitative estimate of prediction accuracy.

19 highly polygenic traits, but not genome-wide prediction accuracy.

20 ion codes have not yet been tested for their prediction accuracy.

21 the multiple traits together may improve the prediction accuracy.

22 chosen from the reference set confirmed high prediction accuracy.

23 rent techniques be used together to maximize prediction accuracy.

24 eal-time polymerase chain reaction with high prediction accuracy.

25 asured by the IDP coefficients and incidence prediction accuracy.

26 -validation methods were applied to quantify prediction accuracy.

27 is a flexible and powerful tool to maximize prediction accuracy.

28 d are the key requisite when aiming for high prediction accuracy.

29 nformational changes have a strong impact on prediction accuracy.

30 terpolating prediction rule has near-optimal prediction accuracy.

31 ping can lead to significant improvements in prediction accuracy.

32 score normalization procedure to improve the prediction accuracy.

33 n by 39 times without causing degradation in prediction accuracy.

34 t omics data to increase metabolic phenotype prediction accuracy.

35 stress-related genes, with markedly improved prediction accuracy.

36 different modeling algorithms to improve the prediction accuracy.

37 enome-wide markers and consistently improves prediction accuracy.

38 omputational costs but also for boosting the prediction accuracy.

39 discarded, as well as the resulting loss in prediction accuracy.

40 typing and phenotyping) in order to maximize prediction accuracy.

41 r paralogs, is most likely to lead to higher prediction accuracy.

42 ls and was found to considerably improve the prediction accuracy.

43 act integration] that influenced the contact prediction accuracy.

44 regions, by using commensurable measures of prediction accuracy.

45 e this type of heterogeneous data to improve prediction accuracy.

46 (SDOH) into risk prediction models improves prediction accuracy.

47 of health-associated genomic data and their prediction accuracies.

48 lected on Escherichia coli and achieved high prediction accuracies.

49 d traits were mostly higher than yield trait prediction accuracies.

50 ygenic model shows promising improvements in prediction accuracies.

51 biomarkers with significant improvements on prediction accuracies.

52 pproaches were used and compared in terms of prediction accuracy: (1) whole-genome prediction (WGP) u

53 la: see text] at k = 6 gave the highest host prediction accuracy (33%, genus level) with reasonable c

54 A random forests model with high prediction accuracy (80%) showed that the strongest modi

55 To further add functionality and increase prediction accuracy- a machine learning binary classifie

56 ain interpretable prediction rules with high prediction accuracies and to successfully extract signif

57 g training populations that maximize genomic prediction accuracy and (2) to reduce the cost of phenot

58 l for human RBP binding estimation with good prediction accuracy and a broad application scope.

59 Creating an ensemble of trees improves prediction accuracy and addresses instability in a singl

60 ting state-of-the-art algorithms in terms of prediction accuracy and biological significance of the p

61 e find that this choice optimises short-term prediction accuracy and can rapidly detect salient fluct

62 the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the

63 s were treated independently suffer from low prediction accuracy and difficulty of biological interpr

64 n improved transcription factor binding site prediction accuracy and dramatically reduced computation

65 ons can be used to further improve the spike prediction accuracy and generalization performance of th

66 alidated SCD risk prediction model with >70% prediction accuracy and incorporates risk factors that a

67 Both the prediction accuracy and interpretability of a classifier

68 parameterizable metaheuristic that improves prediction accuracy and offers greater computational per

69 anatomy ontology improved the candidate gene prediction accuracy and optimized them for predicting ca

70 wever, ML-based RV still faces challenges in prediction accuracy and program accessibility.

71 ess identification of 2D materials with high prediction accuracy and real-time processing capability.

72 refore, the FN-RAST enjoys both satisfactory prediction accuracy and some broad applicability.

73 Systematic comparison of the prediction accuracy and specificity of the different int

74 tperformed existing methods in terms of both prediction accuracy and stability.

75 BE-IDC accommodates both the prediction accuracy and the computational speed that are

76 ting complex phenotypes, increasing both the prediction accuracy and the extent of discernible mechan

77 ds to analytical results quantifying maximum prediction accuracy, and allows the estimation of the ne

78 However, most of them show limited prediction accuracy, and the number of common predicted

79 ly affecting model performances reveals that prediction accuracies are most strongly influenced by th

80 ineering and filtering steps using phenotype prediction accuracy as a metric.

81 scale drug discovery test dataset equivalent prediction accuracy as a random forest.

82 ch significantly improves on microRNA-target prediction accuracy as assessed by both mRNA and protein

83 We measured prediction accuracy as the correlation between actual an

84 TurboFold II also has comparable structure prediction accuracy as the original TurboFold algorithm,

85 own catalytic residue predictors can improve prediction accuracy as well as provide improved ranked p

86 To increase prediction accuracy as well as to provide a means to gai

87 uences, our model significantly improves the prediction accuracy at each of the three steps.

88 The best prediction accuracy AUC = 78.2% (95% confidence interval

89 nal approaches, DrugComboExplorer had higher prediction accuracy based on in vitro experimental valid

90 riants into genomic models slightly improves prediction accuracy because of extensive linkage.

91 ming models for each classification achieved prediction accuracies between 81.5-99%, indicating the p

92 empirical field experiments, we compared the prediction accuracy between multi-kernel physiological a

93 dentified by MarkRank not only have a better prediction accuracy but also have stronger topological r

94 ur rhythm features not only improved models' prediction accuracy but also provided better interpretab

95 forward network (FN) models can provide high prediction accuracy but lack broad applicability.

96 a large scale of contaminant pool with high prediction accuracy, but we can also identify valuable b

97 s while performing PCA and also improved the prediction accuracy by 34% when using linear discriminat

98 of a subject's reference sample can improve prediction accuracy by as much as 14 %, for the H3N2 coh

99 tperforms label propagaton and achieves high prediction accuracy by efficiently capturing local netwo

100 genome prediction (WGP) methods can increase prediction accuracy by making use of a huge number of va

101 supervised learning further improves contact prediction accuracy by making use of sequence profile, c

102 ses in a single-pass screen and confirm high prediction accuracy by means of orthogonal, secondary va

103 Moreover, we further increase the prediction accuracy by transferring the deep learning mo

104 In addition, higher prediction accuracies can be obtained by performing base

105 ogeneous class of elements, greater than 98% prediction accuracy can be achieved in a balanced, compl

106 would be possible, for which cases, and what prediction accuracy can be achieved, are currently open

107 find that deep networks had higher decoding prediction accuracy compared to baseline models.

108 r deep 3DCNN achieves a two-fold increase in prediction accuracy compared to models that employ conve

109 d genomic data showed 35 to 169% increase in prediction accuracy compared to models with only genomic

110 an important problem in biology, but the low prediction accuracy compels us to propose new computatio

111 On MNIST and Zalando Fashion, prediction accuracy consistently improves when escalatin

112 ng multiple random effects, we show that the prediction accuracy could be further improved.

113 rs' performance was evaluated in terms of PS prediction accuracy, covariate balance achieved, bias, s

114 than established risk scores with increased prediction accuracy (decreased Brier score by 10%-25%).

115 Prediction accuracy differed and was better for out-of-h

116 ed with environmental co-variables gave high prediction accuracy due to high genetic correlation betw

117 This model is capable of improving prediction accuracy due to the tolerance of the noise de

118 r organelles were resolved, with exceptional prediction accuracy (estimated at >92%).

119 uantification within all biofluids with high prediction accuracy (expressed as root-mean-square error

120 pancy, YOD, and FH variables achieved an 84% prediction accuracy for >=50% reduction in drinking.

121 ; conversely, the latter strategy sacrifices prediction accuracy for a wider application, since speci

122 RTK II [P = .01]) than prediction by chance; prediction accuracy for all other molecular parameters w

123 tive framework to improve the candidate gene prediction accuracy for anatomical entities by combining

124 em cell SELEX-Seq data, MPBind achieved high prediction accuracy for binding potential.

125 the data of this training set indicated high prediction accuracy for biomass yield.

126 LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial ta

127 g multiple traits together could improve the prediction accuracy for correlated traits.

128 The prediction accuracy for height by the aid of BMI improve

129 Prediction accuracy for Hginorg and HgDOM strongly depen

130 AM and SGB) are capable of delivering a high prediction accuracy for land susceptibility to wind eros

131 w that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude

132 nning economic traits, and provide desirable prediction accuracy for quantitative traits, with univer

133 variate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder,

134 rotein-protein interactions, we reach a high prediction accuracy for such a diverse dataset outperfor

135 and tongue cancer datasets lead to improved prediction accuracy for the metastasis of primary cervic

136 k is validated by reporting degradation type prediction accuracy for the pixel level prediction at th

137 Our prediction accuracy for this multi-label task is 97.61%.

138 ermutation tests revealed above chance-level prediction accuracy for trait-level educational attainme

139 mic regions associated, and estimate genomic prediction accuracies (GPA) for VS traits.

140 ccuracy of 82.0% while solvent accessibility prediction accuracy has been raised to 90% for residues

141 However, the DeltaDeltaG prediction accuracy has only a marginal dependence on th

142 Significant improvements in prediction accuracy have recently been demonstrated thou

143 Prediction accuracy improved by 28.7% for BMI and 10.2%

144 The prediction accuracy improved when they were combined in

145 n was broadened to its top three most likely predictions, accuracy improved to 80%.

146 ntly increased genetic variances and genomic prediction accuracies in 3 production traits compared to

147 We find that prediction accuracies in excess of 80% of the theoretica

148 ent task contrasts or data sources increased prediction accuracies in some but not all cases.

149 ximum ${r^2}$ of 0.86; comparable with other prediction accuracies in the literature despite a signif

150 the-art approaches, our methods yield higher prediction accuracy in 10-fold cross-validation and de n

151 ods, AnnoPred achieves consistently improved prediction accuracy in both extensive simulations and re

152 n conjunction with deep phenotyping improves prediction accuracy in cardiovascular event prediction i

153 ads to larger training datasets and improved prediction accuracy in phenotype prediction.

154 complexes; (2) MD-MM/PBSA provided the best prediction accuracy in terms of clustering favorable and

155 at the HMMs proposed demonstrate a very good prediction accuracy in terms of controlling both the fal

156 actions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by inc

157 ith amyloid-positive status, we examined PRS prediction accuracy in those who converted to AD.

158 trum of the images, it can provide up to 95% prediction accuracy, in discriminating the physiological

159 In most cases, prediction accuracy increased significantly with the inc

160 s, the greatest improvement in the structure prediction accuracy is achieved when we utilize only 40-

161 However, the prediction accuracy is bounded by the proportion of the

162 od is only slightly reduced when the contact prediction accuracy is comparatively low.

163 SEPIa's average prediction accuracy is limited, with an AUC score (area

164 .02), no significant genetic contribution to prediction accuracy is observed.

165 The extent to which this variability in prediction accuracy is related to differences in samplin

166 native conformations may not be examined and prediction accuracy may be compromised due to sampling.

167 s and identifies features that contribute to prediction accuracy: neighboring CpG site methylation, C

168 brane proteins, the average top L long-range prediction accuracy obtained by our method, one represen

169 The prediction accuracy obtained with tiered learning was fo

170 oss-validation, we have been able to achieve prediction accuracies of (mean absolute error, MAE [95%

171 oteins of diverse architectures and achieves prediction accuracies of 90% on a manually curated datab

172 The prediction accuracies of existing computational algorith

173 Prediction accuracies of grain yield evaluated in four e

174 Prediction accuracies of our models, however, have not y

175 ics-assisted breeding models, the better the prediction accuracies of the models and the more useful

176 The prediction accuracies of the SubMito-XGBoost method on t

177 ning algorithms, XGBoost affords the highest prediction accuracy of >90%.

178 nary classification, CSmetaPred_poc achieves prediction accuracy of 0.94 on CSAMAC dataset.

179 10 docking predictions per benchmark case, a prediction accuracy of 38% is achieved on all 55 cases a

180 We subsequently show that the prediction accuracy of 5- and 10-year mortality based on

181 the GBM showed better performance, with the prediction accuracy of 82.0% and area under curve of 0.8

182 x, beta-strand and coil) secondary structure prediction accuracy of 82.0% while solvent accessibility

183 adjuvant treated populations with an overall prediction accuracy of 89% (39 of 44, p < 0.0001).

184 bility to meet the 95/90-PRT with an overall prediction accuracy of 91%.

185 VM) combined with nested cross-validation, a prediction accuracy of 91.2% was achieved when classifyi

186 For HLA-Upgrade, we reached a prediction accuracy of 92% from low- to high-resolution

187 Notably, our classifiers achieved an overall prediction accuracy of 96% for 212 clinical isolates fro

188 d as 1251 ms and 1400 ms, respectively, with prediction accuracy of 96.7% (95% confidence interval, 8

189 in 2 different SSM/PCA components yielded a prediction accuracy of 98%.

190 In this study, we tested the prediction accuracy of AD, mild cognitive impairment (MC

191 ch, this approach significantly improves the prediction accuracy of auditory cortical responses, part

192 It aims to improve the prediction accuracy of basic centrality measures.

193 rget traits affected prediction performance, prediction accuracy of complex traits (grain yield) were

194 many low- and high-frequency components, the prediction accuracy of current popular numerical predict

195 Quantitatively, we observe superior prediction accuracy of diagnostic codes and lab test imp

196 ent trials were used in this study to assess prediction accuracy of different quantitative traits usi

197 and classification methods were compared for prediction accuracy of drug response.

198 ll performance evaluation metrics, while the prediction accuracy of edge-based support vector machine

199 The prediction accuracy of enetLTS was better than that of R

200 With this, the prediction accuracy of fruit forms can be further improv

201 Improved inference and prediction accuracy of GBLUP may be achieved by identify

202 ability under stress conditions; and (3) the prediction accuracy of GE models was found to be superio

203 Our approach achieves 92% prediction accuracy of genome-wide methylation levels at

204 isk score (PRS) approach has shown 75 to 84% prediction accuracy of identifying individuals with AD r

205 machine-learning algorithms may increase the prediction accuracy of immunogenic peptides.

206 quares (PLS) model was constructed, giving a prediction accuracy of more than 95%.

207 pping data for a sequence improves structure prediction accuracy of other homologous sequences beyond

208 ller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduc

209 The prediction accuracy of our model is similar to those rep

210 The method showed a high prediction accuracy of over 90% and very high precision

211 brium or in causal alleles frequencies), the prediction accuracy of polygenic scores can depend on ch

212 (4) We increased SNP-based prediction accuracy of quantitative eye colour.

213 g efforts are focused on improving the class prediction accuracy of SIFTER through expansion of empir

214 l results on S.cerevisiae data show that the prediction accuracy of SON clearly exceeds that of nine

215 Overall, differences in the prediction accuracy of the competing models were small,

216 less, it is still challenging to improve the prediction accuracy of the computational methods.

217 nknown organisms significantly increases the prediction accuracy of the disease status for three of t

218 ng a forward modeling approach, we find that prediction accuracy of the EEG signal also shows the sam

219 The prediction accuracy of the existing methods has signific

220 ts show that it can considerably improve the prediction accuracy of the five centrality measures indi

221 sted R(2) = 0.45), adding TD values improved prediction accuracy of the global variability (adjusted

222 The prediction accuracy of the independent test set M495 was

223 mproved the median five-fold cross-validated prediction accuracy of the model to 0.94 compared to 0.8

224 The gain in prediction accuracy of the multivariate approach is equi

225 oposed framework can effectively improve the prediction accuracy of the pharmacokinetic parameters wi

226 ty changes for all variants, the qualitative prediction accuracy of the Rosetta program reached 65.3%

227 The prediction accuracy of the ROX index increased over time

228 The global quality prediction accuracy of the tool is comparable to other g

229 Prediction accuracy of this new hybrid method was found

230 However, long-term (>5 years) prediction accuracy of this prognosis system needs furth

231 ation accuracy overall; HAPLEXR shows higher prediction accuracy on approximately half of the genes t

232 ing on both genomes improves gene expression prediction accuracy on held out and variant sequences.

233 Furthermore, the overall prediction accuracy on the Nino 3.4 index was better tha

234 auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the puta

235 her demonstrate the improvement of PRS-CS in prediction accuracy over alternative methods.

236 The leave-one-site-out increased average prediction accuracy over pairwise-site for all the trait

237 s show that the new IE function improves the prediction accuracy over the knowledge-based, statistica

238 upstream parameters) by assessing the model prediction accuracy, parameter identifiability and uncer

239 ion model on the same trait resulted in good prediction accuracy (r = 0.65) with 42% of the S/F % var

240 The PLS model produced prediction accuracy (R(2)=0.71, RMSEP=1.33 degrees Brix,

241 Heritabilities ranged from 0.08 to 0.21 and prediction accuracy ranged from 0.01 to 0.33 across 7 di

242 The new EG prediction algorithm shows prediction accuracy ranging from 75% to 91% based on val

243 ivity and specificity for an overall greater prediction accuracy, recalling an average of 10% more an

244 ide association studies (GWAS), genetic risk prediction accuracy remains moderate for most diseases,

245 for both identification and prediction while prediction accuracy scales weakly with the number of lea

246 deep network predictors and achieved top 10 prediction accuracy scores of 75.51% (short range), 60.2

247 r top performing methods with average top 10 prediction accuracy scores of 85.13% (short range), 74.4

248 ength correction produces a 0.976 R(2) value prediction accuracy, significantly higher than the addit

249 tion as a baseline to assess the increase in prediction accuracy stemming from the inclusion of opera

250 resulted in most cases in marginal gains of prediction accuracy, suggesting that later measures migh

251 me models for disease resistance can produce prediction accuracy suitable for application in breeding

252 Genome-wide prediction accuracies tended to be moderate to high (ave

253 Lower prediction accuracy tends to be associated with insuffic

254 hat the resulting meta-model achieves higher prediction accuracy than either model on its own.

255 I-Boost provides substantially higher prediction accuracy than existing methods.

256 F) model was previously shown to have better prediction accuracy than ordinary least square linear re

257 BNNR yields higher drug-disease association prediction accuracy than the current state-of-the-art me

258 ependent model provided better out-of-sample prediction accuracy than the valence-independent model.

259 EAS LUADs had better prediction accuracy than those of European ancestry, pot

260 biological significances and higher average prediction accuracy, than other compared models and meth

261 ntal questions are: (i) What is the limit in prediction accuracy that one can achieve with arbitrary

262 redictions of reference chemicals to compare prediction accuracies to published results from the EPA.

263 han humans and increases the crystallization prediction accuracy to 82.4+/-0.7 % over 77.1+/-0.9 % fr

264 Using genomic prediction accuracy to evaluate importance of marker int

265 dependent test set and resulted in a similar prediction accuracy to that obtained using the training

266 tperform conventional approaches in terms of prediction accuracy, transformation pathway identificati

267 traits (anthesis date and plant height) and prediction accuracy under stress conditions was consiste

268 the first question by testing the limits in prediction accuracy using native contacts as restraints.

269 Prediction accuracy varied across polygenic score approa

270 ML model prediction accuracy was also compared with that of conve

271 ith inaccurate pixelwise manual annotations, prediction accuracy was also evaluated against biologica

272 The relative prediction accuracy was approximately 2.4% for a 0.05-1.

273 In contrast, prediction accuracy was at chance level for depression,

274 Out-of-sample prediction accuracy was comparable for both types of ana

275 The improvement in prediction accuracy was consistent between simulated and

276 Prediction accuracy was high for most models, with cross

277 The prediction accuracy was higher for DeepWAS than for clas

278 thods, which consistently indicated that the prediction accuracy was improved with an R(2) of 0.47-0.

279 The disease prediction accuracy was investigated in a subset of the

280 nding and further demonstrated that callers' prediction accuracy was mediated by citizens' nonverbal

281 The best prediction accuracy was reached by combining (18)F-FDG P

282 Prediction accuracy was similar when using either 1 (wri

283 Prediction accuracy was similarly high in the independen

284 To further boost the prediction accuracy, we extend dRW to dRW-kNN.

285 After achieving high prediction accuracy, we found through the feature extrac

286 rove ranking of catalytic residues and their prediction accuracy, we have developed a meta-approach b

287 The prediction accuracies were examined by five-fold cross-v

288 Between-breed and multi-breed genomic prediction accuracies were low.

289 fication algorithms were used to compare the prediction accuracies when using fitting coefficients as

290 position, growth rate, and gene essentiality prediction accuracy when compared to other methods.

291 ein interaction pairs with approximately 94% prediction accuracy when using sequence and experimental

292 st subset of SNPs that guarantees sufficient prediction accuracy, while also solving the unclear thre

293 bacterial genomes, [Formula: see text] host prediction accuracies with thresholding and consensus me

294 alidation experiment, LMTRDA obtained 90.51% prediction accuracy with 92.55% sensitivity at the AUC o

295 KAML that aims to combine the advantages of prediction accuracy with computing efficiency.

296 n-fold cross validation was used to evaluate prediction accuracy with metrics such as precision, reca

297 inus and frontal sinuses yielded the highest prediction accuracy, with Mucor induced AIFR correlating

298 ividual predictors that improves the overall prediction accuracy, with the in-silico two-hybrid metho

299 drome is about 15%-25%; improvements in risk prediction accuracy would benefit the development and im

300 al model of the bootstrapped sPLS-DA average prediction accuracies yielded optima at 0.005 for resolv