ライフサイエンスコーパス: receiver operating characteristic

1 ogs from those without were calculated using receiver-operating characteristics.

2 ortality or severe morbidity (area under the receiver operating characteristic, 0.77 [0.70-0.83] vs 0

3 o predict AF: increase in the area under the receiver operating characteristic, 0.88 (95% confidence

4 Optimal cutoff from receiver operating characteristics (2.39 mmol/L) showed

5 Receiver operating characteristic analyses determined th

6 s used to analyze changes from baseline, and receiver operating characteristic analyses were used to

7 euromelanin volume was investigated by using receiver operating characteristic analyses, and correlat

8 Mann-Whitney U tests, receiver operating characteristic analyses, Spearman cor

9 rrelations, area under the curve values from receiver-operating characteristic analyses, and diagnost

10 n signed rank, and McNemar tests, as well as receiver-operating-characteristic analyses, were perform

11 Following receiver operating characteristic analysis (Youden's ind

12 and area under the curve with time-dependent receiver operating characteristic analysis for 1-year su

13 Receiver operating characteristic analysis for detecting

14 Receiver operating characteristic analysis for the 3 tau

15 Receiver operating characteristic analysis revealed an a

16 Receiver operating characteristic analysis revealed an a

17 Receiver operating characteristic analysis revealed that

18 Receiver operating characteristic analysis showed an are

19 s performed and CT numbers were subjected to receiver operating characteristic analysis to calculate

20 CT numbers were subjected to receiver operating characteristic analysis to calculate

21 patient subsets and control subjects, and a receiver operating characteristic analysis was performed

22 reviews of PET/CT images was calculated and receiver operating characteristic analysis was performed

23 Receiver operating characteristic analysis was used to a

24 Receiver operating characteristic analysis was used to d

25 Receiver operating characteristic analysis was used to d

26 Multivariate regression analysis and receiver operating characteristic analysis were performe

27 objective was the test performance, based on receiver operating characteristic analysis, and cut-off

28 In receiver operating characteristic analysis, the area und

29 ultivariate prediction model was tested with receiver operating characteristic analysis.

30 city of CLS in determining symptoms based on receiver operating characteristic analysis.

31 ) test, Pearson correlation coefficient, and receiver operating characteristic analysis.

32 ssessed by binary logistic regression and by receiver operating characteristic analysis.

33 performance was evaluated with free-response receiver operating characteristic analysis.

34 ined by histology and to Ishak scoring using receiver operating characteristic analysis.

35 ibution, two-sample test of proportions, and receiver operating characteristic analysis.

36 MFQ clinical cutoff following the results of receiver operating characteristic analysis.

37 Receiver operating characteristics analysis was used to

38 -way ANOVA, logistic regression analysis and receiver-operating characteristic analysis (ROC).

39 Receiver-operating characteristic analysis for SPT and B

40 Receiver-operating characteristic analysis showed that v

41 Receiver-operating characteristics analysis identified a

42 For predicting progression on CT, receiver-operating-characteristic analysis showed area u

43 Receiver-operating-characteristic analysis was performed

44 d after 9-11 wk of erlotinib treatment using receiver-operating-characteristic analysis, linear regre

45 In receiver-operating-characteristic analysis, PET/CT asses

46 At receiver-operating-characteristic analysis, sensitivity

47 On the basis of receiver-operating-characteristic analysis, the optimal

48 lesions for both AR and ER was determined by receiver-operating-characteristic analysis.

49 alue of these parameters was defined using a receiver-operating-characteristic analysis.

50 Receiver operating characteristic and area under receive

51 Accuracy, receiver operating characteristics and area under the cu

52 95.2% sensitivity and 97.6% specificity; the receiver operating characteristic area under curve value

53 rols (no rejection histologically), P<0.001 (receiver operating characteristic area under the curve [

54 t association with sputum eosinophil counts (receiver operating characteristic area under the curve o

55 Receiver operating characteristic area under the curve w

56 -risk coronary computed tomography features (receiver operating characteristics area under the curve

57 [CI]: 1.24 to 2.00; p < 0.0005) with a model receiver-operating characteristic area of 0.69.

58 S and non-NRS plaques, whereas we calculated receiver-operating characteristics' area under the curve

59 The highest receiver operating characteristics-area under the curve

60 Receiver operating characteristics-area under the curve

61 The area under the receiver operating characteristic (AUC) was also high fo

62 te-of-the-art methods in terms of area under receiver operating characteristic (auROC) curve.

63 has been undertaken by using an area under a receiver operating characteristics (AUROC) curve.

64 n-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials

65 ed in the SRL had the highest area under the receiver operating characteristic curve (0.893 [95% CI,

66 radiography, as given by the area under the receiver operating characteristic curve (1.23-fold, P <

67 c accuracy as measured by the area under the receiver operating characteristic curve (AROC).

68 sign of effective sgRNAs with area under the receiver operating characteristic curve (AUC) >0.8, and

69 reening predicted tPE with an area under the receiver operating characteristic curve (AUC) (95% CI) =

70 ents with BE or EAC using the area under the receiver operating characteristic curve (AUC) analysis.

71 We used area under the receiver operating characteristic curve (AUC) as a metri

72 Area under the receiver operating characteristic curve (AUC) is used to

73 tality prediction achieved an area under the receiver operating characteristic curve (AUC) of 0.53 (9

74 ng set with a cross-validated area under the receiver operating characteristic curve (AUC) of 0.807,

75 n cohort, PERSEVERE-XP had an area under the receiver operating characteristic curve (AUC) of 0.90 (9

76 city (95% CI: 76%, 92%), with area under the receiver operating characteristic curve (AUC) of 0.91 wi

77 ty in the test cohort with an area under the receiver operating characteristic curve (AUC) of 0.92.

78 Central reader area under the receiver operating characteristic curve (AUC) values wer

79 nd menopausal status, and the area under the receiver operating characteristic curve (AUC) was comput

80 score were analyzed, and the area under the receiver operating characteristic curve (AUC) was used t

81 Sensitivity, specificity, and area under receiver operating characteristic curve (AUC) were calcu

82 ayer and sector with the best area under the receiver operating characteristic curve (AUC) were ident

83 mination was evaluated by the area under the receiver operating characteristic curve (AUC), and clini

84 the gold standard to compute area under the receiver operating characteristic curve (AUC).

85 terms of odds ratio (OR) and area under the receiver operating characteristic curve (AUC).

86 he GRSs was determined by the area under the receiver operating characteristic curve (AUC).

87 ty was evaluated by using the area under the receiver operating characteristic curve (AUC).

88 The area under the receiver operating characteristic curve (AUC, in g/mL. m

89 In addition, the averaged areas under the receiver operating characteristic curve (AUCs) achieved

90 tivities, specificities, and areas under the receiver operating characteristic curve (AUCs) of PET/CT

91 The area under the receiver operating characteristic curve (AUROC) for QSWP

92 sis (stage 1 or more) with an area under the receiver operating characteristic curve (AUROC) of 0.82

93 imaging achieved a validated area under the receiver operating characteristic curve (AUROC) of 0.98,

94 ens), specificity (Spec), and area under the receiver operating characteristic curve (AUROC) values w

95 Area under the receiver operating characteristic curve (AUROC) values,

96 nation was assessed using the area under the receiver operating characteristic curve (AUROC).

97 ic risk differed by MS group by applying the receiver operating characteristic curve (ROC) cut point.

98 d Early Warning Score (median area under the receiver operating characteristic curve 0.67), and highe

99 l Early Warning Score (median area under the receiver operating characteristic curve 0.71) and electr

100 ac Arrest Risk Triage (median area under the receiver operating characteristic curve 0.73).

101 .74) than a model using MELD (area under the receiver operating characteristic curve = 0.62) or MELD

102 urve = 0.62) or MELD and age (area under the receiver operating characteristic curve = 0.67) to predi

103 re had better discrimination (area under the receiver operating characteristic curve = 0.74) than a m

104 lassifier for AMR was identified (area under receiver operating characteristic curve = 0.84; 95% conf

105 s with a similar reliability (area under the receiver operating characteristic curve = 0.973 [0.838-1

106 erentiating ACR from non-ACR (area under the receiver operating characteristic curve = 90%, 95% confi

107 Results LAS (area under the receiver operating characteristic curve [AUC] = 0.93, P

108 ed risks, (2) discrimination (area under the receiver operating characteristic curve [AUC]) between i

109 sensitivity, specificity, and area under the receiver operating characteristic curve [AUC]) of the nu

110 [18F]flutemetamol PET status (area under the receiver operating characteristic curve [AUC], 0.92) com

111 n low- and high-grade glioma (area under the receiver operating characteristic curve [AUC], 1) for th

112 gher discriminatory accuracy (area under the receiver operating characteristic curve [AUC]: 0.96 and

113 ood accuracy (cross-validated area under the receiver operating characteristic curve [principal + sec

114 Receiver operating characteristic curve analyses and pre

115 isons were performed in template space, with receiver operating characteristic curve analyses to asse

116 Receiver operating characteristic curve analyses were us

117 Binary logistic regression and receiver operating characteristic curve analyses were us

118 A receiver operating characteristic curve analysis (area u

119 preoperative biopsies were reported by using receiver operating characteristic curve analysis and Spe

120 The summary receiver operating characteristic curve analysis demonst

121 Receiver operating characteristic curve analysis evidenc

122 Conventional, frequentist receiver operating characteristic curve analysis was con

123 Receiver operating characteristic curve analysis was use

124 lly overt severe sepsis syndrome patients by receiver operating characteristic curve analysis, with a

125 ict malignant disease was determined using a receiver operating characteristic curve analysis.

126 DIT, and DIS plus DIT with a time-dependent receiver operating characteristic curve analysis.

127 Model discrimination was assessed using receiver operating characteristic curve analysis.

128 es for patient outcome were determined using receiver operating characteristic curve analysis.

129 8.7% and specificity was 77.3% at case-based receiver operating characteristic curve analysis.

130 Receiver operating characteristic curve and the area und

131 The receiver operating characteristic curve area for the glo

132 Receiver operating characteristic curve areas trended lo

133 iagnostic sensitivity and specificity in the receiver operating characteristic curve did not differ b

134 were compared on the basis of nonparametric receiver operating characteristic curve estimations by u

135 Mean validation areas under the receiver operating characteristic curve for discriminati

136 Areas under the receiver operating characteristic curve for early and la

137 The area under the receiver operating characteristic curve for internal and

138 leep quality for concurrent validity and the receiver operating characteristic curve for predictive v

139 The area under the receiver operating characteristic curve for screening be

140 According to the area under the receiver operating characteristic curve for SUVpeak, DIB

141 emic total perfusion deficit areas under the receiver operating characteristic curve for the 2 expert

142 The area under the receiver operating characteristic curve for the diagnosi

143 The area under the receiver operating characteristic curve for the differen

144 Similarly, for non-AC data, areas under the receiver operating characteristic curve for the experts

145 The receiver operating characteristic curve for the full reg

146 ariate random-effects and hierarchic summary receiver operating characteristic curve models.

147 ur prediction method shows an area under the Receiver Operating Characteristic curve of 0.85 for all

148 iagnostic values with maximum area under the receiver operating characteristic curve of 0.878 for CCA

149 elocity-time integral with an area under the receiver operating characteristic curve of 0.938 (0.785-

150 30 days after injury, with an area under the receiver operating characteristic curve of 0.939 in the

151 NLST database demonstrated an area under the receiver operating characteristic curve of 0.963 (95% co

152 -validation Area Under Curve of 0.85 for the Receiver Operating Characteristic curve of our model.

153 The area under the receiver operating characteristic curve of SVC was signi

154 The area under the receiver operating characteristic curve of the King's Co

155 developed de novo HCC with an area under the receiver operating characteristic curve value higher tha

156 ning diet vs controls with an area under the receiver operating characteristic curve value of 0.95 (9

157 liac disease on a GFD with an area under the receiver operating characteristic curve value of 0.96 (9

158 more data becomes available, area under the receiver operating characteristic curve values increase

159 Area under the receiver operating characteristic curve was 0.85 (95% co

160 Area under the receiver operating characteristic curve was 0.88 (95% co

161 Area under the multivariate model receiver operating characteristic curve was 0.881.

162 on-specific enolase (NSE; the area under the receiver operating characteristic curve was 0.91 for tau

163 Area under the receiver operating characteristic curve was 93.2% (95% C

164 7 to June 2013, out-of-sample area under the receiver operating characteristic curve was approximatel

165 (0.5%) and 91.6% (0.1%), the area under the receiver operating characteristic curve was between 0.94

166 s correlation coefficient and area under the receiver operating characteristic curve were 0.581 and 0

167 s limited, with an AUC score (area under the receiver operating characteristic curve) that reaches 0.

168 d to accurately predict (>80% area under the receiver operating characteristic curve) the clinical en

169 nce in some datasets was low (area under the receiver operating characteristic curve, < 0.7) for the

170 ory response syndrome (median area under the receiver operating characteristic curve, 0.60) and Sepsi

171 lure Assessment score (median area under the receiver operating characteristic curve, 0.62), intermed

172 an Failure Assessment (median area under the receiver operating characteristic curve, 0.65) and Modif

173 PD diameter cutoff of 7.2 mm (area under the receiver operating characteristic curve, 0.70; 95% CI, 0

174 with colon-only CD (P = .001; area under the receiver operating characteristic curve, 0.72).

175 improved survival prediction (area under the receiver operating characteristic curve, 0.73 vs 0.60, r

176 complications (overall model area under the receiver operating characteristic curve, 0.77).

177 riple-negative breast cancer (area under the receiver operating characteristic curve, 0.834).

178 AD with dementia vs controls (area under the receiver operating characteristic curve, 0.87, which is

179 with PD and control subjects (area under the receiver operating characteristic curve, 0.92 and 0.88,

180 e, likelihood ratio negative, area under the receiver operating characteristic curve, and by cross-va

181 With a receiver operating characteristic curve, IDO activity ha

182 Receiver operating characteristic curve, Kaplan-Meier me

183 Area under the receiver operating characteristic curve, sensitivity, sp

184 automatically, and so was the area under the receiver operating characteristic curve.

185 d sensitivity and specificity metrics on the receiver operating characteristic curve.

186 stently frequent" trajectory (area under the receiver operating characteristic curve: 0.84, sensitivi

187 ng had a statistically higher area under the receiver operating characteristics curve (AUC) than non-

188 tion method was used to describe the summary receiver operating characteristics curve and bivariate m

189 M65 and M30 both had an area under the receiver operating characteristics curve of 0.84 to esti

190 Receiver operating characteristics curve revealed that r

191 Receiver operating characteristics curve showed aspartat

192 for AMI, as quantified by the area under the receiver-operating characteristic curve (AUC), was compa

193 sensitivity, specificity, and area under the receiver-operating characteristic curve (AUROC) of HBeAg

194 1; P=0.01) and triglycerides (area under the receiver-operating characteristic curve 0.740 versus are

195 acteristic curve 0.740 versus area under the receiver-operating characteristic curve 0.758; P<0.01).

196 sity lipoprotein cholesterol (area under the receiver-operating characteristic curve 0.806 versus 0.8

197 Correlation, Bland-Altman, and receiver-operating characteristic curve analyses were pe

198 Receiver-operating characteristic curve analysis reveale

199 tion cohort, the score had an area under the receiver-operating characteristic curve of 0.87 (p < 0.0

200 pendent predictor of outcome (area under the receiver-operating characteristic curve of the model = 0

201 urrence in the next 48 hours (area under the receiver-operating characteristics curve = 0.88 +/- 0.07

202 tures were compared using the area under the receiver-operating-characteristic curve (AUC).

203 c regression analysis showed areas under the receiver-operating-characteristic curve (AUCs) of 0.78 c

204 Receiver-operating-characteristic curve analyses of the

205 Receiver-operating-characteristic curve analysis of the

206 Area under receiver operating characteristic curves (AUC) and sensi

207 Descriptive statistics and areas under the receiver operating characteristic curves (AUCs) were cal

208 gm, using logistic model and areas under the receiver operating characteristic curves (AUCs).

209 However, receiver operating characteristic curves (ROC) curve ana

210 ed fluid responsiveness with areas under the receiver operating characteristic curves (with 95% CIs)

211 finition based on the highest area under the receiver operating characteristic curves [AUCs] and posi

212 gingivalis (0.23%) and T. forsythia (0.35%), receiver operating characteristic curves analysis demons

213 Receiver operating characteristic curves and areas under

214 Receiver operating characteristic curves constructed usi

215 Receiver operating characteristic curves determined the

216 Mean validation area under the receiver operating characteristic curves for discriminat

217 Analysis of receiver operating characteristic curves implicates aber

218 dentified in models that had areas under the receiver operating characteristic curves of 0.57 (95% CI

219 Pooled sensitivity, specificity, and summary receiver operating characteristic curves of each imaging

220 iver operating characteristic and area under receiver operating characteristic curves revealed CCI to

221 Receiver operating characteristic curves revealed that l

222 Receiver operating characteristic curves summarizing dia

223 Lastly, we used receiver operating characteristic curves to show that se

224 Receiver operating characteristic curves were used to de

225 gression models to calculate odds ratios and receiver operating characteristic curves with area under

226 basis was assessed by using areas under the receiver operating characteristic curves, and difference

227 nstrate that our method has uniformly better receiver operating characteristic curves, and identifies

228 acy were quantified using multilevel models, receiver operating characteristic curves, and test sensi

229 yzed with mixed effects logistic regression, receiver operating characteristic curves, and the Fisher

230 Using receiver operating characteristic curves, diffusion char

231 sion-weighted imaging scores (area under the receiver operating characteristic curves, respectively,

232 Density cutoffs were determined using receiver operating characteristic curves.

233 itivity to be predicted were calculated with receiver operating characteristic curves.

234 DeLong method for statistical comparison of receiver operating characteristic curves.

235 We determined optimal thresholds using receiver operating characteristic curves.

236 no significant differences in area under the receiver operating characteristic curves.

237 libration, and area under the curve (AUC) of receiver operating characteristic curves.

238 Discriminatory value was assessed by using receiver operating characteristic curves.A total of 2882

239 nd Scotland by assessing the areas under the receiver operating characteristics curves (ROC-AUCs).

240 Area under the receiver operating characteristics curves to detect ball

241 fy intraretinal and SRF using area under the receiver operating characteristics curves, precision, an

242 te gadolinium enhancement was compared using receiver operating characteristics curves.

243 Areas under the receiver-operating characteristic curves of the 2 differ

244 thod at predicting ischemia (areas under the receiver-operating characteristic curves, 0.87 versus 0.

245 n the epicardial myocardium (areas under the receiver-operating characteristic curves, 0.87 versus 0.

246 t statistically significant (areas under the receiver-operating characteristic curves, 0.90 versus 0.

247 The receiver-operating characteristic demonstrated that miR-

248 acy were measured by using the free-response receiver operating characteristic method and the receive

249 iver operating characteristic method and the receiver operating characteristic method for nodule dete

250 Random-effects and hierarchical summary receiver operating characteristic model meta-analyses we

251 The area under the receiver operating characteristic of Systemic Inflammato

252 to SEA with ECFP on ChEMBL20 and equivalent receiver operating characteristic performance.

253 Cross-validated receiver operating characteristic (ROC) analyses were pe

254 Receiver operating characteristic (ROC) analysis demonst

255 Analysis of variance (ANOVA) and receiver operating characteristic (ROC) analysis reveale

256 Receiver operating characteristic (ROC) analysis was per

257 Receiver operating characteristic (ROC) analysis was use

258 using paired t tests, analysis of variance, receiver operating characteristic (ROC) analysis, and ex

259 ial least squares discriminant analysis, and receiver operating characteristic (ROC) analysis.

260 DFF for grading steatosis were assessed with receiver operating characteristic (ROC) analysis.

261 ients and healthy controls using RT-qPCR and receiver operating characteristic (ROC) analysis.

262 c generalized linear mixed-effect models and receiver operating characteristic (ROC) analysis.

263 ark datasets and three legacy datasets using Receiver Operating Characteristic (ROC) and Precision Re

264 kers and EMR data achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0

265 imulated datasets in terms of area under the receiver operating characteristic (ROC) curve (AUC), num

266 Receiver operating characteristic (ROC) curve analysis w

267 ami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis.

268 The area under the receiver operating characteristic (ROC) curve for case-c

269 e used the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for perfor

270 The mean of the area under the receiver operating characteristic (ROC) curve for the cl

271 from viral pathogens with an area under the receiver operating characteristic (ROC) curve of 0.73 (9

272 +/- 0.7% and 85 +/- 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 +/

273 ROCker employs the receiver operating characteristic (ROC) curve to minimiz

274 Receiver operating characteristic (ROC) curve was drawn

275 For each test, we generated a receiver operating characteristic (ROC) curve, and calcu

276 rformance, as measured by the area under the receiver operating characteristic (ROC) curve, relative

277 -to-lymphocyte ratio (MLR) were optimized by receiver operating characteristic (ROC) curve.

278 Comparison of receiver operating characteristic (ROC) curves demonstra

279 re mapped against the consensus equation and receiver operating characteristic (ROC) curves produced.

280 Receiver operating characteristic (ROC) curves were anal

281 Receiver operating characteristic (ROC) curves were cons

282 Receiver operating characteristic (ROC) curves were cons

283 Receiver Operating Characteristic (ROC) curves were obta

284 CT HU and BV/TV for identification of TMJOA, receiver operating characteristic (ROC) curves were plot

285 Receiver operating characteristic (ROC) curves, category

286 Using receiver operating characteristic (ROC) curves, we deter

287 controls were calculated and compared using receiver operating characteristic (ROC) curves.

288 tive approach for software optimization uses receiver operating characteristic (ROC) curves.

289 oronary artery stenosis was determined using receiver operating characteristic (ROC) curves.

290 und in human kinesin motor domains using the receiver operating characteristic (ROC).

291 By receiver operating characteristics (ROC) analysis, cFFR

292 Ten-fold cross-validation was used for the receiver operating characteristics (ROC) analysis.

293 Odds ratios (ORs) and areas under receiver-operating characteristic (ROC) curves (AUCs) we

294 Receiver-operating-characteristic (ROC) analysis was per

295 ts on outcome prediction were compared using receiver-operating-characteristic (ROC) curve analysis a

296 n mortality and survival (the area under the receiver operating characteristic [ROC] curve [AUROC] fo

297 eters were calculated for each question, and receiver operating characteristic statistics were genera

298 In receiver operating characteristics, the calculated area

299 The area under the receiver operating characteristic was similar whether qu

300 Using 7 metabolites improved the receiver operating characteristic with area under the cu