ライフサイエンスコーパス: false-positive

1 did not actually have a retinal detachment (false-positive).

2 number of pharmaceuticals (22) with only one false positive.

3 ptamers, and viral RNA domains with a single false positive.

4 tients were culture negative and potentially false positive.

5 re packages reported a substantial number of false positives.

6 de of tRNA space and flags them as candidate false positives.

7 pped to a reference genome to further reduce false positives.

8 lytical thinking increases the prevalence of false positives.

9 tudies and have a higher likelihood of being false positives.

10 ography (LDCT) screening, may greatly reduce false positives.

11 detecting known strong interactions with no false positives.

12 itives, but also by decreasing the number of false positives.

13 se additional flagged features were verified false positives.

14 y 2.2% of MARGI-identified interactions were false positives.

15 se new algorithms detect significantly fewer false positives.

16 drug-target pairs, which introduces a lot of false-positives.

17 out any matrix effect, cross-reactivity, and false-positives.

18 he later progressive diseases on CT, with no false-positives.

19 There were 52 true-negative (29%) and 17 false-positive (10%) (18)F-FDG PET/CT studies.

20 treatment cases were more likely to be Xpert false-positive (45/321 Xpert-positive retreatment cases

21 d accordingly produced the highest number of false positives (6).

22 te constraint to prevent the accumulation of false positives across large-scale data sets.

23 an-assay interference compounds (PAINS) with false-positive activities in assays often propagate thro

24 ercent identity, can reduce the frequency of false-positive alignments more than 20-fold compared wit

25 86% specific for cardiac ATTR amyloid, with false positives almost exclusively from uptake in patien

26 46% of Xpert-positives with CT> 30 would be false positive, although 70% of false positives would be

27 ties than traditional LC-MS/MS, produced one false positive and did not detect 6 confirmed compounds.

28 which we show are partly responsible for the false positive and false negative compound identificatio

29 False positive and false negative peaks detected from ex

30 owever, many of these tools suffer from high false positive and false negative rates.

31 se deficiency, but this test has substantial false positive and false negative rates.

32 Our results revealed pitfalls caused by false positive and lineage-differential copy number vari

33 thresholds resulting in an unknown number of false positive and negative matches.

34 still suffers from non-negligible numbers of false positive and negative SNV and INDEL calls that wer

35 uspicious nodules may be helpful in avoiding false positives and altering the extent of treatment whe

36 e found TIN adjustment had better control of false positives and false negatives (sensitivity = 0.89,

37 d fair-to-poor correlation, with evidence of false positives and false negatives in the microarray da

38 enging to develop; attenuating the number of false positives and false negatives under high-throughpu

39 These results show that snoReport 2.0 avoid false positives and false negatives, allowing to predict

40 utralize RNA degradation effects by reducing false positives and recovering biologically meaningful p

41 e positive and 24.3% negative; there were 14 false-positive and 29 false-negative scans.

42 th good histopathologic correlation although false-positive and false-negative cases exist.

43 with a statistical method that accounts for false-positive and false-negative errors to test deer sa

44 calculation of true-positive, true-negative, false-positive and false-negative patients as classified

45 wever, for gelatin, problems associated with false-positive and false-negative results, inconsistenci

46 n, technical parameters, number of true- and false-positive and true- and false-negative results were

47 nability to multiplex targets, high rates of false positives, and (in some cases) the requirement of

48 the confidence in calls, reduce the risk of false positives, and help characterize complex events.

49 of the analysis or produce broad impact eQTL false positives, and the tendency of methods that accoun

50 nning with an over-motivated state with many false positives, and transitioning through a more or les

51 ty indices </=20% for fixation loss, 15% for false-positives, and 33% for false-negatives.

52 atched spectra in spite of potential risk of false positive annotations emerging from automation.

53 False positives are limited using the introduced Sequent

54 gy for these purposes because the chances of false positives are small owing to the use of a mass spe

55 , in terms of increased accuracy and reduced false positive as well as false negative rates.

56 s correlation typically inflates the rate of false positive associations.

57 taking them into consideration could lead to false-positive associations.

58 be predicted at a threshold of 0.34 without false positives at a sensitivity of 56% at 12 hours afte

59 g/L as a threshold associated with almost no false positives at acceptable sensitivity.

60 lated our models to estimate the impact of a false-positive BFV epidemic in 2013.

61 The assay mitigates false positives by selectively identifying positive hits

62 Five cases were false-positive by Xpert MTB/RIF in patients with nontube

63 tion sequencing (NGS) data is susceptible to false positive calls due to sequencing, mapping and othe

64 ble efforts in predicting VC concordance and false positive calls in low-concordance regions which un

65 next generation sequencing can help diminish false positive calls, but this does not ameliorate poten

66 To better distinguish true from false positive calls, we present a method that uses geno

67 There were two false-positive calls in 534 samples with no known subchr

68 n errors could generate tens of thousands of false-positive calls per genome.

69 specificity of 95% (58/61), caused by three false-positive calls with ARMS-PCR.

70 minations identified 42.9% (39 of 91) of the false-positive cases to be the same lesion as the IBC.

71 To minimise false-negative and false-positive classifications, recommended methods for

72 Sunnyvale, CA) found no false-negative and 4 false-positive cobas Cdiff test results.

73 er speed also reduced both true-positive and false-positive colorectal polyp identification.

74 est statistics was simulated for the desired false positive control to avoid excess false positives w

75 Consequently, standard false-positive control procedures, such as the Bonferron

76 False-positive detection, acute infection during the win

77 lects fewer invasive pneumonias versus fewer false-positive diagnoses due to less secretions and/or l

78 Outcomes included number of infants with false-positive diagnoses linked to ART per 1,000 ART ini

79 matory testing, 1/1,000 ART initiations were false-positive diagnoses.

80 10% of infants who initiate ART may reflect false-positive diagnoses.

81 ll challenging and affected by high rates of false-positive diagnoses.

82 eason score of 3+4) and caused 11 additional false-positive diagnoses.

83 tory testing, 128/1,000 ART initiations were false-positive diagnoses; with confirmatory testing, 1/1

84 d infants incorrectly treated with ART after false-positive diagnosis (e.g., medication toxicities);

85 tion experiments confirm that XGSA can avoid false positive discoveries, while maintaining good stati

86 unexplained variability in mutation rates on false-positive driver gene predictions.

87 BP responses but are not more likely to have false-positive DSE results.

88 al shortcomings, including susceptibility to false positives due to artifactual peaks, poor localizat

89 e a matched total DNA input control to avoid false positives, effectively decreasing the sequencing c

90 ng, they also detect a problematic number of false positive EIC peaks and can also fail to detect rea

91 cific reasons why XCMS and MZmine 2 find the false positive EIC peaks that they do and in what ways t

92 ed procedure is able to properly control the false positive error rate at the nominal level.

93 (random sets of genes) to estimate power and false-positive error rate of methods applied to simulate

94 recently developed models which also include false positive errors (i.e. species detected in places w

95 as they do not account for allelic dropout, false-positive errors and coverage nonuniformity.

96 Furthermore, our analysis can exclude 'false positive' events of cellular overlap and extracell

97 ined with digital mammography (DM) decreases false-positive examinations and increases cancer detecti

98 reatment patients with CT> 30; however, most false positives fall below this cut-point.

99 The true-positive, false-positive, false-negative, and unconfirmed rates fo

100 They also identified fewer false-positive features at faster speeds (42 of 115; 36.

101 % and 96.4%, respectively, for R2 (one fewer false-positive finding).

102 r risk are sensitive to modeling choices and false-positive findings are a threat.

103 ions] vs 60% [69 of 115 lesions]), and fewer false-positive findings than MR imaging (five vs 45) (P

104 The most common cause of false-positive findings was nutrient foramina (106 of 27

105 % and 92.9%, respectively, for R1 (six fewer false-positive findings) and 92.3% and 96.4%, respective

106 tive predictive value for HCC (R1, two fewer false-positive findings).

107 d reporting data made it too easy to publish false-positive findings.

108 For this analysis, ZIKAV IgM was considered false positive for samples interpreted as a DENV infecti

109 CA) on 91/99 specimens that were recorded as false positive (FP) or false negative (FN) compared to t

110 luded cancer detection rate (CDR), number of false-positive (FP) recalls, and incremental CDR for eac

111 ty, as indicated by the false-negative (FN), false-positive (FP), and fixation loss (FL) rates, on gl

112 Assess the impact of false-positives (FP), false-negatives (FN), fixation los

113 rom 54% to 93%) in 10- to 12-year-olds and a false-positive fraction up to 35% in older subjects.

114 Overall false-negative and false-positive fractions were 22% and 2%, respectively;

115 e often insufficient to completely eliminate false positives from environmental samples, which are es

116 igher sensitivity than Aptima, but with more false positives from pharyngeal samples.

117 False positives from structural OCT can be mitigated wit

118 .18-3.83) and had a predicted probability of false positive HCC greater than 10% regardless of larges

119 mL at transplant yielded a 50% lower risk of false-positive HCC (odds ratio [OR], 0.45; 95% confidenc

120 The risk of false-positive HCC is markedly higher in certain groups,

121 Transplant centers with high false-positive HCC rates may benefit from greater oversi

122 False-positive HCC was defined as answering "no" to the

123 cant among-center variability in the rate of false-positive HCC was seen.

124 ed T2 MELD exceptions, of which 245 (6%) had false-positive HCC.

125 ltiple DNA cleavage events can be a cause of false positive hit identification.

126 ed bioenergetic shunt that greatly minimizes false-positive hits, we identify mitoxantrone out of mor

127 s can deliver a multitude of data, including false-positive hits.

128 pplied to ligand screening in the context of false-positive hits.

129 ble to distinguish between true-positive and false-positive homology groups.

130 the highest selectivities, yielding only one false positive; however, it was bias toward the most int

131 ely large fluorescence tags and the risk of 'false positive' identification when analyzing these rare

132 nd peptide retention prediction filtering of false positive identifications.

133 The scan was considered false-positive if no primary lesion was found correspond

134 However, bidirectional promoters scored as false positives in CRISRPi.

135 resulting in improved power and control for false positives in EWAS.

136 To reduce this overflow of false positives in next-generation sequencing (NGS) scre

137 datasets and estimated a potential source of false positives in one dataset.

138 ovided from this bacterium in order to avoid false positives in the frame of the detection and the qu

139 ient method to find true positives and avoid false positives in vertebrate organisms.

140 ity and low rate of both false-negatives and false-positives in this approach.

141 In particular, the number of false positives increased with the level of missing data

142 e of the tested compounds may be measured as false positive inhibitors with the much-utilized ThT ass

143 ent years, most PPI networks still have many false positive interactions and false negative edge loss

144 A list of non-specific and false positive interactors is presented, based on re-occ

145 False positive late-onset ADHD cases are common without

146 true-positive lesions in five patients and a false-positive lesion in one patient.

147 Two different false-positive lesions were identified with PET/unenhanc

148 gest that disseminated NTM disease may cause false-positive LF-LAM results.

149 hese spoilage species are liable to frequent false positives, long culture times and fungal contamina

150 n subjects with F0-F2 fibrosis, the rates of false-positive LSM results for F3-F4 fibrosis increased

151 False-positive mammograms and benign results on biopsy d

152 paration step that results in the calling of false-positive minority variants.

153 this methodology leads to identification of false-positive mutations.

154 hat the proposed method has low fractions of false positive/negative bouton detections (2/0 out of 18

155 False-positives obtained with RCM in photodamaged skin a

156 d and HaMStR respectively were classified as false positives on experimental data set.

157 In conclusion, IEB may result in false positive or negative genetic associations in very

158 t observed in convenience set samples and no false positive or negative identifications were observed

159 It can also be a rate-limiting step if high false positive or negative rates necessitate multiple ro

160 n of drugs in low concentrations and risk of false positive or negative results caused by mixed spect

161 The increasing number of reports about false positive or negative results from conventional cyt

162 r groups as well as seven adult controls; no false positives or negatives were identified.

163 Using four marker peptides, no false-positive or false-negative results were obtained.

164 biopsies, or other procedures performed for false-positive or indeterminate surveillance results.

165 with cirrhosis experience physical harm for false-positive or indeterminate surveillance tests-more

166 linked to and retained in care for 10 years (false-positive) or lifelong (true-positive).

167 periments and that this variability leads to false-positive peak calls.

168 ding XCMS-online and MZmine2, yield numerous false-positive peak detections.

169 how differences between target compounds and false-positive peaks as high as 74%, as was the case for

170 We use this approach to show a reduction in false-positive peaks as well as improved consistency acr

171 Such analyses can produce a large number of false positive predictions, suggesting that sites suppor

172 s, despite an even more tremendous growth in false positive predictions.

173 redicting CRM activity, but is also prone to false positive predictions.

174 ingle chromatin marks leads to high rates of false-positive predictions.

175 ional 9 true positives being discovered at a false positive probability of 0.2 and 5 additional true

176 al design and analysis parameters can reduce false positives, provide greater resolution of species i

177 es of Crohn disease, showing how it controls false positives, provides power similar to that achieved

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

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

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

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

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

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

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

185 4-5 with a positive predictive value of 99%, false positive rate of 0.5%, and a sensitivity of 48%.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

221 High false-positive rates and cost of additional investigatio

222 False-positive rates for progression in normal eyes usin

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

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

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

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

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

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

229 Once the anti-HBc alone pattern is detected, false-positive reactivity should be ruled out and furthe

230 e task that can result in missed cancers and false-positive recalls.

231 95%CI, 0.57-0.70), and a higher frequency of false-positive recommendations for peptide-receptor radi

232 of genomic copy number highlighted potential false-positive regions, thus emphasizing the importance

233 d malignancies; however, false negatives and false positives remain major limitations.

234 retention time prediction, text-mining based false positive removal/true positive ranking, chemical t

235 dered noteworthy after the correction by the false-positive report probability.

236 TBDRplus performed on positive cultures, the false-positive resistance rate for direct testing of MTB

237 No false-positive response is generated when the sensors ar

238 -6 dB) loss, primarily owing to an elevated false-positive response rate.

239 target compound can be differentiated from a false-positive response.

240 A new approach to reduce the false-positive responses commonly encountered in the fie

241 ith different error properties; it minimizes false positives resulting from mapping errors and other

242 In either case, we found a high level of false positive results and a general lack of correlation

243 ing standard colorimetric assays often shows false positive results and has little correlation to the

244 sma samples that were HIV negative showed no false positive results in the detection of HIV-1 p24 ant

245 We here used proteomics to characterise false positive results occurring in the ERM as being due

246 edictive value of CMV PCR in saliva was 59%; false positive results were associated with lower viral

247 f 10 adenomas (90% sensitivity), without any false-positive results (100% positive predictive value).

248 Rates of false-positive results (121.2 per 1000 women [95% CI, 10

249 ult in 15840 true-positive results and 15960 false-positive results (positive predictive value, 50%).

250 y 100%; 95% CI 88.4-100) with two additional false-positive results (specificity 99.9%; 99.7-100).

251 n additional 3 deaths, but yielded 1988 more false-positive results and 11 more overdiagnoses per 100

252 We found that CERES decreased false-positive results and estimated sgRNA activity for

253 , increasing concerns have been raised about false-positive results entering the literature.

254 Commercial ELISA kits are known to give false-positive results for OTA concentrations when pheno

255 nt of genetic dependency, thereby leading to false-positive results in copy number-amplified regions.

256 hreshold of alpha = 2.5% for controlling for false-positive results or type 1 error, regardless of th

257 per into the tissue block, and occurrence of false-positive results using immunohistochemistry alone.

258 All specimens with false-positive results were found to contain stx1 or stx

259 itis (>/=1 site with PD >/=4 mm), hardly any false-positive results were identified.

260 To explore reasons for false-negative and/or false-positive results, we used pfhrp2/3-specific PCR an

261 otracer, as well as conditions that engender false-positive results.

262 publication bias assessments and can lead to false-positive results.

263 ble-helix DNA strands (e.g., 47 nt) minimize false-positive results.

264 utations while yielding the fewest number of false-positive results.

265 cers (IBCs) detected after a negative versus false-positive screening among women participating in th

266 91 of 1302) were detected among women with a false-positive screening as the most recent breast imagi

267 ing a negative screening as the reference, a false-positive screening examination increased the risk

268 ade CIN and, almost exclusively, represented false-positive screening findings.

269 th a negative (the reference group) versus a false-positive screening were estimated by using logisti

270 P = .03) compared with women with a previous false-positive screening with benign biopsy.

271 and 2.8 (95% CI: 1.8, 4.4) for women with a false-positive screening without and with needle biopsy,

272 ompared with those detected after a previous false-positive screening.

273 irected evolution (RDE2) screen that negates false-positive selection.

274 False-positive serology for Lyme disease was reported in

275 False-positive staining for herpes zoster antigen was de

276 In both groups of patients, false-positive staining for herpes zoster antigen was de

277 False-positive staining was also detected on some extra-

278 tal herpes is associated with a high rate of false-positive test results and potential psychosocial h

279 varying amounts of CCDs sufficient to cause false-positive test results up to 2 kUA/L with nonglycos

280 As a consequence of a false-positive test, 65 individuals required at least on

281 Harms were sensitive to the rates of false-positive testing and the frequency of liver biopsy

282 merically more frequent harms resulting from false-positive testing.

283 ients, 150 (95% CI, 146-154) had one or more false-positive tests equating to a number needed to harm

284 nosed with infectious mononucleosis based on false-positive tests for primary Epstein-Barr virus infe

285 score separation between true positives and false positives than earlier versions.

286 /CT resulted in no false negatives and fewer false positives than the other imaging techniques.

287 45/321 Xpert-positive retreatment cases were false-positive) than new cases (40/461) (14% [95% confid

288 tions and predicting arguably higher quality false positives that are located nearby the native bindi

289 ed by interference compounds, artifacts, and false positives that permeate the pool of initial hits.

290 The systematic error of false-positive tissue misclassification was low, occurre

291 ect over 90% of essential genes with minimal false positives using a compact 5 sgRNA/gene library.

292 ands; hGal-3C-25 of 25; hGal-7-28 of 30); no false positives were detected.

293 o results) with LC-MS; on the other hand, 10 false positives were obtained elaborating data deriving

294 False-positives were mainly lymph node lesions.

295 r missing data in one source, and can reduce false positives when multiple sources highlight the same

296 ng correction can generate a large number of false positives while multi-testing correction tremendou

297 NMR methods for detecting false positives will be analyzed on the basis of their p

298 sired false positive control to avoid excess false positives with the usage of an asymptotic chi-squa

299 Of these, 6 were likely to be false positives, with the remaining 50 commencing with a

300 30 would be false positive, although 70% of false positives would be missed.