ライフサイエンスコーパス: false-positive rate

1 correct classification, 100% specificity, 4% false positive rate).

2 dding quality control steps and lowering the false positive rate.

3 r data without incurring an inflation of the false positive rate.

4 thin the middle of reads, while reducing the false positive rate.

5 ipts in a tissue-specific manner, with a low false positive rate.

6 ds for each motif group and thus control the false positive rate.

7 edious process but is associated with a high false positive rate.

8 ion genes at higher precision and a very low false positive rate.

9 in advance-93% true positive rate with a 0% false positive rate.

10 eats, consistency of performance, speed, and false positive rate.

11 ampling and coalescence times, to reduce the false positive rate.

12 personal specific splice junctions at a low false positive rate.

13 genomes, balancing high sensitivity and low false positive rate.

14 , with an 89% true positive rate, and an 11% false positive rate.

15 s, but it nevertheless tends toward a higher false positive rate.

16 egression in terms of power of detection and false positive rate.

17 state-specific antigen (PSA) test has a high false positive rate.

18 sequencing data, but also has a much higher false positive rate.

19 on novel variants had a significantly higher false positive rate.

20 tein interactions at the expense of only 19% false positive rate.

21 ation in genome-wide scans results in a high false positive rate.

22 ments across the whole genome for a very low false-positive rate.

23 CT images with a high sensitivity and a low false-positive rate.

24 sequence capture assay has an extremely low false-positive rate.

25 pitation sequencing (CLIP-seq) to reduce the false-positive rate.

26 ar3 marked cancerous lesions with a very low false-positive rate.

27 nd is the most powerful test for a specified false-positive rate.

28 increased true-positive rate and a decreased false-positive rate.

29 so proposed a list of filters to control the false-positive rate.

30 onella LPS or flagellum, resulting in a high false-positive rate.

31 specificity, moderate sensitivity and a low false-positive rate.

32 of subjects, suggesting an unacceptably high false-positive rate.

33 es with a 6% false-negative rate and a 0.66% false-positive rate.

34 s additional variance to avoid inflating the false-positive rate.

35 tioning strategy, with a properly controlled false-positive rate.

36 best sensitivity as well as good control of false-positive rate.

37 m benign prostatic hyperplasia and have high false positive rates.

38 ts of population structure resulting in high false positive rates.

39 genomes, we obtain estimates of the methods' false positive rates.

40 onal or not, and consequently result in high false positive rates.

41 etitive in small alignments and with relaxed false positive rates.

42 h high sensitivities and maintained moderate false positive rates.

43 e of the art, while keeping a lower level of false positive rates.

44 t computational prediction methods have high false positive rates.

45 gorithms with high statistical power and low false positive rates.

46 ns in sets of isogenic samples with very low false positive rates.

47 the data adaptive method in order to compare false positive rates.

48 a false-positive peak and may help to reduce false-positive rates.

49 es with single-nucleotide resolution and low false-positive rates.

50 tical visual inspection and still yield high false-positive rates.

51 luated the effect of group size on true- and false-positive rates.

52 s last method can lead to underestimation of false-positive rates.

53 ate-of-the-art methodology while controlling false-positive rates.

54 d small false discovery rates and acceptable false-positive rates.

55 entalist to have causal predictions with low false-positive rates.

56 suffering from limited sensitivity and high false-positive rates.

57 s studies, which could have yielded elevated false-positive rates.

58 n mutation identification and a reduction in false-positive rates.

59 s after a return of spontaneous circulation (false-positive rate, 0.02; 95% CI, 0.01-0.06; summary po

60 sory-evoked potentials between days 1 and 7 (false-positive rate, 0.03; 95% CI, 0.01-0.07; positive l

61 ence of corneal reflexes more than 24 hours (false-positive rate, 0.04; 95% CI, 0.01-0.09; positive l

62 , 4.87-16.08), myoclonic status epilepticus (false-positive rate, 0.05; 95% CI, 0.02-0.11; positive l

63 , unfavorable electroencephalogram patterns (false-positive rate, 0.07; 95% CI, 0.04-0.12; positive l

64 r score showing extensor posturing or worse (false-positive rate, 0.09; 95% CI, 0.06-0.13; positive l

65 2.16), and elevated neuron-specific enolase (false-positive rate, 0.12; 95% CI, 0.06-0.23; positive l

66 [CI, 0.04 to 0.09]; false-negative rate, 5%; false-positive rate, 11%).

67 on," the specificity was considerably lower (false-positive rate, 18.5%).

68 ve rates (82% and 88%, respectively) and low false-positive rates (19% and 8%).

69 rocalcification clusters, with an acceptable false-positive rate (2.7 per breast view).

70 [CI, 0.04 to 0.11]; false-negative rate, 5%; false-positive rate, 24%).

71 ld be 3 to 4 percentage points higher with a false-positive rate 30 times greater if women with faile

72 overestimated the amount of PR when RF<20% (false-positive rate 36%; 95% CI: 18-57%).

73 suggests that the algorithm has a stable low false positive rate (~4%) and high true positive rate (>

74 rmation of the compound identity, with a low false positive rate (9%).

75 As a result, pKWmEB effectively controlled false positive rate, although a less stringent significa

76 ype of 96% of all stimuli, with less than 5% false positive rate and a ~20ms error in timing.

77 eproducibility, sensitivity, prioritization, false positive rate and computational time.

78 ark its performance (i.e. precision, recall, false positive rate and correlation) in comparison with

79 ition, assays were performed to estimate the false positive rate and demonstrated high confidence of

80 prove diagnostic performance by reducing the false positive rate and improving the positive predictiv

81 ate by simulations that MOMENT shows a lower false positive rate and more robustness than existing me

82 accurate in QTN effect estimation, had less false positive rate and required less computing time tha

83 ith the use of cfDNA had significantly lower false positive rates and higher positive predictive valu

84 to its better control of false negative and false positive rates and its ability to quantify RNAi ef

85 Clinicians should be cognizant of false positive rates and seeding point errors as common

86 This was mainly because of high false positive rates and seeding point errors.

87 hip between various methods and compared the false positive rates and statistical power using both si

88 elationship between methods and compared the false positive rates and statistical power using both si

89 False-positive rate and false-negative rate for small in

90 with >90% sensitivity and specificity at 20% false-positive rate and false-negative rate thresholds.

91 udies and show that it has a well-controlled false-positive rate and more power than existing mixed-m

92 Existing methods suffer from high false-positive rates and are unable to effectively diffe

93 High false-positive rates and cost of additional investigatio

94 nomics has consistently been plagued by high false-positive rates and divergent predictions.

95 DELISHUS achieves significantly lower false-positive rates and higher power than previously pu

96 sed but have their drawbacks, including high false-positive rates and limited antibody availability,

97 om exome-sequencing data are limited by high false-positive rates and low concordance because of inhe

98 We assessed false-positive rates and power for parametric and non-pa

99 aphy (sensitivity, false-positive rate [ FPR false-positive rate ], and cancer detection rate [ CDR c

100 Screening performance (sensitivity, false-positive rate) and diagnostic accuracy (95% confid

101 redictive value to predict poor recovery (0% false-positive rate), and provided equal performance to

102 r trisomy 21 had higher sensitivity, a lower false positive rate, and higher positive predictive valu

103 g these constraints can dramatically inflate false positive rates, and often leads researchers to dra

104 The true-positive rate, false-positive rate, and accuracy (95% confidence interv

105 tions (defined as <30% fixation losses, <30% false-positive rates, and <30% false-negative rates) wer

106 Differences in true-positive rates, false-positive rates, and mammographic findings were ass

107 r harms of LDCT are radiation exposure, high false-positive rates, and the potential for overdiagnosi

108 spatial proximity with high sensitivity, low false-positive rates, and tunable detection distances.

109 False positive rates appear to be low, as PilFind predic

110 cy (for our benchmark, the true positive and false positive rates are 73% and 29%, respectively).

111 False positive rates are estimated and controlled by per

112 For the same false-positive rate as Hemoccult II (0.98%), the true-po

113 fractures at high sensitivity and with a low false-positive rate, as well as to calculate vertebral b

114 There is a high false-positive rate associated with many of these tests

115 We benchmarked MIPA's false positive rate at less than 1%.

116 the proposed procedures properly control the false positive rate at the nominal level.

117 ts, while also maintaining the type I error (false positive) rate at the nominal level.

118 f risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% in

119 suggested that pRSEM has a greatly decreased false-positive rate at the expense of a small increase i

120 a 5% improvement in true positives at the 5% false-positive rate at the residue level.

121 , a method was developed for determining the false-positive rate (background) signal.

122 main advantages of DISCOVER-seq are (i) low false-positive rates because DNA repair enzyme binding i

123 False-positive rates before arbitration were 61.1 per 10

124 The difference in false-positive rates between cultures from babies and ad

125 screpancy, the false-negative rates, and the false-positive rates between patient and surrogates were

126 y predicted poor neurologic outcome with low false-positive rates: bilateral absence of pupillary ref

127 VarScan and SNVer had generally lower false positive rates, but also significantly lower sensi

128 erogeneity; and an underestimation of actual false positive rate by Benjamini-Hochberg correction.

129 average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively.

130 bjects, this bias can decrease the voxelwise false-positive rate by more than 30% in the control grou

131 tration rate less than 60 mL/min/1.73 m, the false-positive rate can be reduced when estimated glomer

132 e of false-negative rates in addition to the false-positive rates common to all Bloom filter-based ap

133 IsoMut, when tuned correctly, decreases the false positive rate compared to conventional tools in a

134 milar sensitivity (recall), but a much lower false positive rate compared to less specific CNV caller

135 the IDOL library resulted in uniformly lower false positive rates compared to competing libraries, wh

136 ts are more precise, showing greatly reduced false-positive rates compared to the alternative approac

137 and have high sensitivity with extremely low false-positive rates compared with the well-established

138 ASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy.

139 However, high false-positive rates, costs, and potential harms highlig

140 With tomosynthesis, the false-positive rate decreased from 85% (989 of 1160) to

141 The false-positive rate did not differ significantly between

142 f false negatives were computed and only the false positive rates differed significantly, ranging fro

143 ction is a weighted sum of true-positive and false-positive rates divided by incidence, as estimated

144 s, to identification of false detections and false positive rate estimation.

145 variants one-by-one, leading to intractable false positive rates, even with vast samples of subjects

146 sclerosis case collection and determined the false-positive rate expected when comparing such a colle

147 her USPSTF screening recommendations; harms (false-positive rates, false-negative rates, surgery rate

148 e to their incomplete CDS, leading to higher false positive rate for lncRNA identification.

149 False positive rates for mortality were less than 5% for

150 cator; although some variables have very low false positive rates for poor outcome, multimodal assess

151 161 cases (5.6%; 95% CI: 1.0%, 10%), and the false-positive rate for CO-RADS category 5 was one of 28

152 cartilage, with a 91% true-positive and 13% false-positive rate for differentiating Beck score 1 car

153 The median tipping point (maximum acceptable false-positive rate for extracolonic findings) was calcu

154 tion programs tested, and Infernal has a low false-positive rate for non-coding gene detection.

155 False-positive rates for progression in normal eyes usin

156 odds ratio (DOR), heterogeneity in DOR, and false positive rate (FPR) for each signature using bivar

157 ined by means of next-generation sequencing (False Positive Rate (FPR), 3.5%; R5- or X4 tropic varian

158 screening-detected breast cancer (SDC), and false-positive rate (FPR) before and after consensus mee

159 ssociated genes is greatly improved, and the false-positive rate (FPR) for non-causal tissues is well

160 5% confidence interval [CI]: 83%, 97%), at a false-positive rate (FPR) of 10.8 per patient (95% CI: 6

161 mance of screening mammography (sensitivity, false-positive rate [ FPR false-positive rate ], and can

162 uence-based calls of X4 variants (Geno2Pheno false-positive rate [FPR] of </=2%) formed distinct line

163 formance (detection rates [DR] for specified false-positive rates [FPR] and vice versa).

164 (false negative rate, FNR 5%) and accuracy (false positive rate, FPR 1x10(-)(5)).

165 y the same as those of the LASSO method; the false positive rates (FPRs) of DBN were averagely 46% le

166 Tau cutoffs had low false-positive rates (FPRs) for good outcome while retai

167 Sensitivity for fixed false-positive rates (FPRs) was reported for neonatal ou

168 o account 1, 2, and 3 isotopes decreases the false positive rate from 22, 2.8 to <0.3%, but the cost

169 ased CNV callers are available, however, the false positive rates from automated calling are commonly

170 functional miR-TSVs is difficult due to high false positive rates; functional miRNA recognition seque

171 point for radiologic follow-up occurred at a false-positive rate greater than 99.8% (interquartile ra

172 henol A, caffeine, NP, OP, and triclosan had false positive rates >15%.

173 te (ie, the hit rate or specificity) and the false-positive rate (ie, the false-alarm rate or 1 - sen

174 e overall detection rate was 95% with a 0.1% false-positive rate if 20% of women were selected to rec

175 east one of the following problems: (i) high false-positive rate; (ii) long running time; (iii) work

176 The false positive rate in 140 patients with laboratory conf

177 The pixel prediction false positive rate in healthy plants gets as low as 1.4

178 uracy as OR-AC-GAN, and the pixel prediction false positive rate in healthy plants is 1.57%, which is

179 rning strategy (DeepBGC) that offers reduced false positive rates in BGC identification and an improv

180 ibutions are anti-conservative and have high false positive rates in some scenarios, although the emp

181 False-positive rate in 52 normal controls was 2%.

182 llenging, because it necessitates a very low false-positive rate in read mapping.

183 more effective than trimming in reducing the false-positive rate in single nucleotide polymorphism (S

184 cing data analysis since masking reduces the false-positive rate in SNP calling without sacrificing t

185 of factors that might influence the elevated false-positive rate in the neonates including patient de

186 the potential harms of treatment (ie, higher false-positive rates in low-prevalence populations) as s

187 The false-positive rate is approximately 0.033%.

188 ons remains required, because a considerable false-positive rate is noticed.

189 0.1-mL remnant with 5% false-negative and 1% false-positive rates is less than 1 s.

190 tional picking methods while maintaining low false-positive rates, is capable of picking challenging

191 old enrichment of true positives at the 0.05 false-positive rate level.

192 on F measure, which combines sensitivity and false positive rate, Look4TRs outperformed TRF and MISA-

193 sitivity, from less than 45% up to 94%, at a false positive rate < 11% for a set of 47 experimentally

194 had the best outlier detection accuracy with false positive rates < 0.05 and high sensitivity, and en

195 High NSE cutoff values with false positive rates </=5% and tight 95% confidence inte

196 ecificity (>90%), but the false-negative and false-positive rates makes the test suboptimal for preva

197 in 12.5 min, with a 95% recovery and a zero false positive rate (n = 15).

198 al validation set of 58% (95% CI, 51-65%) at false positive rate of 0% (CI, 0-7%).

199 atabase show a detection rate of 93.6% and a false positive rate of 0.16 per hour (FP/h); furthermore

200 4-5 with a positive predictive value of 99%, false positive rate of 0.5%, and a sensitivity of 48%.

201 ghly malignant electroencephalography had an false positive rate of 1.5% with accuracy of 85.7% (95%

202 rs found 90 false peak pairs, representing a false positive rate of 4.4%.

203 with a sensitivity of 48% (CI, 45-51%) at a false positive rate of 5% (CI, 0-15%) in the external va

204 At a False Positive Rate of 5%, our method determines true po

205 icted with sensitivities of 63% and 58% at a false positive rate of 6% and 7% at 12 and 24 hours, res

206 At 24 hours, sensitivity of 65% with a false positive rate of 6% was obtained.

207 H), achieving a validation rate of 82% and a false positive rate of 8%.

208 Our goal was to reduce the false positive rate of CM diagnosis, and so the algorith

209 f reporter ions fragments, which reduces the false positive rate of incorrectly assigned cross-linked

210 ikelihood-based error modeling to reduce the false positive rate of mutation discovery in exome analy

211 roughput of 100,000 particles/s and a record false positive rate of one in a million.

212 ly in metagenomic data sets that reduced the false positive rate of plasmid detection compared with t

213 ified that allow a good, albeit at about 14% false positive rate of sepsis diagnosis.

214 showed that both the true positive rate and false positive rate of the proposed detection method do

215 While most compounds had overall false positive rates of </=5%, bisphenol A, caffeine, NP

216 etect all aneuploid cases with extremely low false positive rates of 0.09%, <0.01%, and 0.08% for tri

217 100% sensitivity for outbreak isolates, with false positive rates of between 9% and 22%.

218 he primary end point was a comparison of the false positive rates of detection of fetal trisomies 21

219 t a reference genome are susceptible to high false positive rates of homology detection.

220 -level performance during the game, (2) True/False positive rates of subjects' decisions, and (3) Mut

221 We find false positive rates of templated mutagenesis in murine

222 he specificity was 99.9% (99.7-99.9), with a false-positive rate of 0.14% (0.06-0.33).

223 achieved a true-positive rate of 0.91 and a false-positive rate of 0.14.

224 achieved a true-positive rate of 0.83 and a false-positive rate of 0.17.

225 fidence interval [CI]: 87.0%, 98.9%), with a false-positive rate of 0.29 per patient.

226 of 26 findings; 95% CI: 0.72, 0.96), with a false-positive rate of 1.3.

227 of 60 findings; 95% CI: 0.79, 0.94), with a false-positive rate of 1.6.

228 g-point for invasive follow-up occurred at a false-positive rate of 10% (IQR, 2 to >99.8%).

229 actures were confirmed in 74, representing a false-positive rate of 16%.

230 itivity of 79% and specificity of 81% with a false-positive rate of 19.4%.

231 onfidence interval [CI]: 0.68, 0.90), with a false-positive rate of 2.5 findings per patient.

232 of 107 findings; 95% CI: 0.75, 0.87), with a false-positive rate of 2.7.

233 , benign, or normal findings, resulting in a false-positive rate of 29.6%.

234 ment (n = 2), leading to an overall CrAg LFA false-positive rate of 34%.

235 82% of de novo single base mutations with a false-positive rate of about one error per Gb, resulting

236 on positively correlates with the behavioral false-positive rate of face choices.

237 Because of the high false-positive rate of LDCT, antibiotics should be regar

238 c, and prognostic value and could reduce the false-positive rate of LDCT, thus improving the efficacy

239 We formalize how to minimize the false-positive rate of miBFs when classifying sequences

240 seful adjunct to pDUS because it reduces the false-positive rate of pDUS.

241 est approach that envisioned controlling the false-positive rate of study results over many (hypothet

242 d success as they all suffered from the high false-positive rate of target prediction results.

243 curate than PClouds, Augustus has the lowest false-positive rate of the coding gene prediction progra

244 were performed to investigate the power and false-positive rate of this procedure, providing recomme

245 oid wheat, we were also able to estimate the false-positive rate of this strategy as 0 to 28% dependi

246 We used artificial sequences to evaluate the false-positive rates of a set of programs for detecting

247 on by history of coronary heart disease, the false-positive rates of association tests will be close

248 tion of enhancers predicted by ENCODE reveal false-positive rates of at least 70%.

249 The high false-positive rates of CT (20%) and PET/CT (9%) resulte

250 array-based methods is still required due to false-positive rates of prediction algorithms.

251 nces as negative controls for evaluating the false-positive rates of prediction tools, such as gene i

252 mammograms, the sensitivity (P = .039), FPR false-positive rate (P = .004), and CDR cancer detection

253 ologist yielded significant increases in FPR false-positive rate (P = .011) and CDR cancer detection

254 ate of error discovery without affecting the false positive rate, particularly within the middle of r

255 On average, 0.5 false-positive rate per view were microcalcification clu

256 idence interval: 81%, 94%), with 2.7 +/- 1.8 false-positive rate per view, 62 of 72 lesions detected

257 haliana transcriptome does not influence the false positive rate performance of nine widely used DGE

258 e show that our method has a well-calibrated false-positive rate, performing well with ChIP-seq data

259 rue-positive rate ranging from 3% to 57% for false-positive rates ranging from 0.00001 to 0.001, resp

260 Furthermore, the system has a very low false-positive rate resulting in a precision of up to 99

261 e of any work-ups had consistently lower FPR false-positive rate , sensitivity, and CDR cancer detect

262 ctive value was higher (25.8% vs. 18.2%) and false positive rate significantly lower in the ALARMS ON

263 sed approaches, have been suffered from high false positive rates since the NES consensus patterns ar

264 The high false-positive rate suggests a potential period where ph

265 number of SNPs but with a considerably lower false positive rate than other methods.

266 ed that LASSO had the higher power and lower false positive rate than the other three methods.

267 n RepeatScout and ReCon and has a much lower false positive rate than WindowMasker.

268 gests that SQDIA results in a markedly lower false-positive rate than standard DIA: 5 for SQDIA and 8

269 rning architectures are capable of producing false-positive rates that are orders of magnitude lower

270 With a 10% false-positive rate, the genetic score alone detected 19

271 Diagnostic focus was associated with false-positive rate; the odds of a false-positive findin

272 ilter, and is also able to tolerate a higher false-positive rate, thus allowing us to correct errors

273 CT resulted in a five-fold reduction of LDCT false-positive rate to 3.7%.

274 ng characteristic (ROC) curves, and true and false positive rates (TPR and FPR).

275 sion analysis and compared true positive and false positive rates (TPR/FPR).

276 g medications in mutation carriers, although false-positive rates, unneeded imaging, and unneeded sur

277 ans suspect sepsis, yet are low-yield with a false-positive rate up to 50%.

278 disease incidence trends produced increased false-positive rates (up to 0.15 at alpha=0.05) under st

279 (empirical simulations), while not inflating false-positive rate using a study with biological replic

280 e (<10%) of vision abnormalities showed high false-positive rates (usually >75%).

281 extracolonic malignancy per 600 cases with a false-positive rate varying across scenarios from 0% to

282 The false positive rate was 79.8 per 1000 screenings.

283 The VFs were included if the false-positive rate was <=20% and false-negative rate wa

284 The false-positive rate was 93 of 834 (11.2%) for all cases,

285 although not statistically significant, the false-positive rate was higher in FMM (9.1%) than in FBB

286 The aggregate false-positive rate was higher in the 65+ cohort than in

287 The false-positive rate was lower for DBT than for DM in all

288 False positive rates were 0.06% (95% CI, 0.03 to 0.11) i

289 s 0.997, true-positive rates were >0.99, and false-positive rates were <0.001.

290 False-positive rates were higher for a Glasgow Coma Scal

291 False-positive rates were higher for women with risk fac

292 Importantly, false-positive rates were not affected by selection bias

293 BiFET's ability to increase power and reduce false positive rate when compared to hypergeometric test

294 sent in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity.

295 sfully reveal a network structure with a low false positive rate while still capturing non-linear and

296 For trisomies 21 and 18, the false positive rates with cfDNA testing were significant

297 y for invasive cancers, and the reduction in false-positive rates with DBT in prospective trials indi

298 re compared in terms of cancer detection and false-positive rates with the corresponding FFDM plus DB

299 A major risk of CT screening is a high false-positive rate, with associated risks and costs ass

300 in low positive predictive values (PPVs) and false-positive rates, with a lack of precision in accura