ライフサイエンスコーパス: false-positive

1 motif acts as an NES (true positive) or not (false positive).

2 in rodents but underperform in humans (i.e., false positives).

3 -2 produced 100% clinical specificity and no false positive.

4 end-of-treatment (18)F-FDG PET/CT scans were false-positive.

5 analysis to distinguish true positives from false positives.

6 miliar with the diagnostic pitfalls to avoid false positives.

7 umptions that are often violated, leading to false positives.

8 h had 57% sensitivity but with 14 times more false positives.

9 sis onset and penalizes late predictions and false positives.

10 to the expectation due to a large number of false positives.

11 o prioritize preannotated markers and reduce false positives.

12 igher values of K and yields high numbers of false positives.

13 e or higher power but also robust control of false positives.

14 inimizers from the genome to avoid excessive false positives.

15 ethods but this resulted in a high number of false positives.

16 NuSeT improves nuclear detection and reduces false positives.

17 similarly, although one assay produced more false positives.

18 m downstream changes, while greatly reducing false positives.

19 n candidate gene literature are likely to be false positives.

20 Ts for confirmation, which may have included false positives.

21 a miR371 expression (true positives) with no false positives.

22 glomeruli in nephrectomy samples, with 10.4% false positives.

23 screening tests, showed a high percentage of false positives.

24 ss dosing thus likely reducing the number of false positives.

25 onal tools lack consistency and are prone to false positives.

26 iments, our original design yielded numerous false positives.

27 tistical specificity, reducing the number of false positives.

28 in many clinical scenarios it is hampered by false positives.

29 t, multiple statistical testing may increase false positives.

30 10(6) B. pertussis genomes/mL and showed no false-positives.

31 e-specific mutability, thereby yielding many false-positives.

32 rs such as (18)F-PSMA, is required to reduce false-positives.

33 mechanistic investigations, we show that the false-positive 18F-FDG-PET/CT result for detecting nodal

34 -100%) and specificity (86-90%) and very low false positives (6-10%) and negatives (< 5%), and it als

35 s were independently adjudicated as true- or false-positive ACS events.

36 To reduce false-positive alarm rates and improve the accuracy of a

37 In this sense, reducing (or suppressing) false positive alarms is hugely desirable.

38 d illicit substance detection are subject to false-positive alarms because of this inaccuracy and the

39 onversion to nAMD and 47 (93.2%) represented false-positive alerts.

40 ble HIT despite negative HIPA and 2 possible false-positive algorithm predictions.

41 False positives also varied by class: 20% for Br, 37% fo

42 ivity or recall) with maintenance of nominal false positive and false discovery rates compared the ot

43 clude covariates, and also maintains nominal false positive and false discovery rates in its posterio

44 and/or have issues with maintaining nominal false positive and false discovery rates.

45 riments can result in significantly inflated false positive and false discovery rates.

46 f the PPI networks by reducing the number of false positive and false negative interactions and is be

47 erative examination was assessed in terms of false positive and false negative rates.

48 mate of the model variance, and thus lead to false positive and false negative results when the numbe

49 To minimize false positive and false negative test results in popula

50 th strict settings to minimize the number of false positive and negative peaks in a data set, gap fil

51 and the proportion of patients with true and false positive and negative results.

52 ariants in a conservative manner to minimize false positive and negative variants in the target genom

53 e reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives.

54 This can result in false positives and disrupt the accuracy of fine-mapping

55 ff-target background fluorescence, decreases false positives and enables accurate RNA profiling in un

56 ty of HRM-based approaches for mitigation of false positives and false negatives in dPCR.

57 n of mammograms is affected by high rates of false positives and false negatives(2).

58 gression) do not consider, which can lead to false positives and false negatives.

59 n resistance mutations reduces the number of false positives and identifies a G70D mutation in the Rp

60 cells with uniform amplification to decrease false positives and increase sensitivity for mosaic muta

61 id and portable; however, they often display false positives and lack sensitivity.

62 These methods tend to detect a lot of false positives and often lack of power when the effect

63 t, that simultaneously decreased the risk of false positives and retained superior power.

64 Due to their high rate of false positives and the need to meet zero tolerance leve

65 dards lack precision, presenting issues with false positives and unneeded surgical intervention for p

66 computational motif algorithms often lead to false-positive and -negative predictions.

67 ereas VRC with a 5% threshold resulted in 29 false-positive and 10 false-negative findings.

68 Lung-RADS resulted in nine false-positive and 16 false-negative findings, whereas V

69 sed in screening settings, resulting in high false-positive and false-negative calls.

70 , and via evaluation of potential sources of false-positive and false-negative HTR events.

71 al data, leading to high likelihoods of both false-positive and false-negative inferences.

72 Artifacts can lead to false-positive and false-negative interpretation of prog

73 ia-specifically the removal of VFs with high false-positive and false-negative rates and entries with

74 producing screening results with much lower false-positive and false-negative rates especially with

75 treatment, lower associated morbidity, fewer false-positive and false-negative results, lower-cost, a

76 isting approaches are likely to produce both false-positive and false-negative results, resulting in

77 by considering the clinical implications of false-positive and false-negative results.

78 There were 10 false-positive and four false-negative detections with t

79 lable for discovery (gamma), and the type 1 (false-positive) and type 2 (false negative) error rates

80 an interpretation of false progression (ie, false-positive), and 39.6% (38/96) had no effect on the

81 VIA reliability and reproducibility, reduced false positive, and introduced peer-to-peer education an

82 cal workflows, harm resulting from potential false positives, and identifying the appropriate scope o

83 ion procedures that can reduce the number of false positives, and the challenges associated with thes

84 effect loci, candidate gene studies prone to false positives, and underpowered genome-wide associatio

85 ak performance for predicting true-positive, false-positive, and negative examinations (AUC range, 0.

86 ic) do not account for this bias and inflate false positive associations.

87 e association studies (GWAS) and can lead to false-positive associations.

88 ated with caution, such as the potential for false positives because of the exploratory nature of the

89 The SWV values of false positive benign lesions, such as: granulomatous ma

90 ualis human infection, and it notably gave a false-positive Blastomyces DNA probe laboratory result.

91 rticipants underwent PET-CT imaging based on false-positive blood tests, and 0.22% underwent a futile

92 PTLD, given the observed high proportions of false-positives both at interim and at end-of-treatment

93 microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide

94 Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform f

95 rtions, whereas over-amplification increased false positive calls.

96 Two false-positive cases of LR-5 included a cholangiocarcino

97 There were 2 (10%) false-positive cases with PLG, in which the final pathol

98 inst detection of colonization, resulting in false positive catheter-associated urinary tract infecti

99 filtering guidelines (to reduce the rate of false-positive claims that a variant is disease related)

100 visual assessment of SUVr images can reduce false-positive classification in this population.

101 benefit (a weighted sum of true positive and false positive classifications) of using the model, with

102 evels, which can lead to severe inflation of false-positive colocalization findings.

103 t statistics in order to achieve the desired false positive control and was compared to the asymptoti

104 ions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and

105 alternating laser excitation, which reduces false positive cross-correlation and facilitates comappi

106 for appropriate disposition of patients with false-positive CT findings.

107 ance-most likely because of a high number of false-positive decisions by the Deauville score.

108 ngue virus and SARS-CoV-2, which can lead to false-positive dengue serology among COVID-19 patients a

109 Failing to consider COVID-19 due to false-positive dengue serology can have serious implicat

110 lso show that the pH-sensitive probes reduce false positive detection rates in a mouse model of non-c

111 ing the detection threshold while minimizing false positive detection rates.

112 These false-positive diagnoses have profound consequences for

113 n of statistics, including the assessment of false positive differences in parametric versus permutat

114 atures in human cancer; (iii) information on false-positive discovery rate of commonly used bioinform

115 e complexity and the potential for causing a false-positive DNA barcoding paradox have been underesti

116 e dropout or variance in sequence coverage), false positives (due to read errors) among mutation call

117 These data demonstrate the false positive effects of TA and EGCG on inhibiting TMEM

118 bility of elimination, leading to premature (false-positive) end-of-epidemic declarations.

119 an outcome of interest, if unaccounted for, false positives ensue.

120 high power while accounting for the overall false positive error rate.

121 oorganisms in ancient rocks, thereby leaving false-positive evidence for early life in the geological

122 ence of intraretinal hemmorhage predicting a false-positive examination (adjusted odds ratio, 3.86; 9

123 Conclusion The benefits of reduced false-positive examinations and higher specificity with

124 (< 50 years, P = .025) were associated with false-positive examinations.

125 edge is an effective approach to eliminating false positive features, prioritizing functionally impac

126 The 1 patient with false-positive findings had a marginal negative CRM of o

127 nd malignant bone lesions, which can lead to false-positive findings on (68)Ga-PSMA-11 PET.

128 stases that were 6 mm or larger with limited false-positive findings using postcontrast T1-weighted M

129 included, to assess the risk of introducing false-positive findings when using advanced reconstructi

130 Adding mammography increased false-positive findings without any additional cancer di

131 ering steps that can minimize the chances of false positive-findings due to sex-specific sequencing e

132 han culture and, notably, identifies samples false positive for Salmonella spp.

133 n HCoV species, a Pan-CoV assay would return false positives for as few as 1% of asymptomatic adults,

134 We also found a high proportion of false positives for hypoxaemia in Peru (11.6%, 95% CI 7.

135 WHO cutoffs, we found that the proportion of false positives for tachypnoea increased with altitude:

136 ematic because of the discovery of excessive false positive (FP) mutations when sequencing picogram q

137 greater fixation loss but a similar level of False Positives (FP) as the HFA.

138 idirectional sequencing was performed for 24 false-positive (FP) and 3 false-negative (FN) specimens.

139 reening outcomes, including rates of recall, false-positive (FP) findings, biopsy, cancer detection r

140 g the true-positive rate (TPR) and number of false-positive (FP) findings.

141 False-positive (FP) or 'type I error' cases, and false-n

142 provided a detection sensitivity of 87% with false positives (FPs)/scan of 0.42.

143 Specificity was 94.2% (false-positive fraction [FPF], 5.8%; 1388 of 24 020) for

144 h in which we demonstrate a 10% reduction of false positives from 2.5 million analyses.

145 rent algorithms do not sufficiently identify false-positive fusions arising during library preparatio

146 y other methods, while calling 10-fold fewer false-positive fusions in nontransformed human tissues.

147 levels and large increases in the number of false-positive genes and transcripts.

148 or identification of both false-negative and false-positive germline large insertions and deletions.

149 25 D+ and 50 D- (22 recipients from D- with false positive HIV tests).

150 By differentiating true and false positives, HRM enables determination of the optima

151 SQDIA reduced false-positive identifications, compared to experiments

152 vity spectral deconvolution, leading to less false-positive identifications.

153 This leads to an elimination of most of the false positives identified by the sulfatide assay.

154 resulted positive, while we identified zero false positive in 250 controls.

155 However, the definition of a false positive in CAFA has not fully accounted for the o

156 tives in 78% and 41% of individual eyes, and false positives in 56% and 17% of individual eyes at the

157 False positives in bioinformatic searches of the genome

158 A common source of false positives in drug discovery is ligand self-associa

159 set reliably identifies false negatives and false positives in high-quality SV callsets from short-,

160 from limitations in terms of robustness and false positives in peptide matching.

161 nual analysis, DeepSqueak was able to reduce false positives, increase detection recall, dramatically

162 rculation in the United States and found one false positive, indicating a specificity of 99.90%.

163 rate, in simulations, that CAUSE avoids more false positives induced by correlated horizontal pleiotr

164 The risk of obtaining false positives is exacerbated by wide interindividual h

165 g >1000 autoantigens have been attributed to false positives (Landegren, 2019).

166 rior detection rate was an increased rate of false positive lesions with an increase in the false dis

167 l TBR (4.10 +/- 1.17 vs. 2.99 +/- 1.01) than false-positive lesions at the early time point (P < 0.01

168 primary prostate cancer, an equal number of false-positive lesions was observed among the different

169 entified at both time points; however, fewer false-positive lesions were detected at the delayed time

170 across the species' range, and that the low false positives make the output of the algorithm amenabl

171 included 50 screening-detected cancers, 1787 false-positive mammograms, and 384 benign biopsy results

172 to meet both objectives: (i) avoid excessive false-positive matches and (ii) maintain the minimizer m

173 Upon repeat testing, only a single false-positive MCR-2 producer remained, as the isolates

174 sion of unmethylated cytosines can introduce false positive methylation call.

175 reoperative MRI outcomes (ie, true positive, false positive, negative) using univariate (ie, Fisher e

176 rt against any culture-positive result, with false positives of <1% and 5.5% for Xpert and Ultra.

177 Adjusting the parameters to eliminate false positives often excludes true particles in certain

178 ted another 8 cases of ON invasion that were false positive on histopathology (accuracy: 63.3%; sensi

179 viral load, suggesting utility in mitigating false positive or false negative results of direct SARS-

180 lculated and error types were categorized as false positives or negatives.

181 of providing a relatively increased risk of false-positive or -negative results.

182 mportant information that could help exclude false-positive or false-negative results.

183 either prioritizing accuracy (low number of false positives) or completeness (low number of false ne

184 ection technique can reduce the incidence of false positives originating from mispriming events.

185 sults: Among 56 participants, 13 (22.8%) had false-positive osseous (68)Ga-PSMA-11 findings and 43 (7

186 by certain chemical structures resulting in false positive outcomes.

187 hreshold probabilities (0.8, aiming to avoid false-positive poor outcome attribution), that the max-I

188 rrent approaches also often suffer from high false positive prediction rates.

189 on seed binding can lead to a high level of false-positive predictions.

190 hat the approach allows drastic reduction of false positive quantitations and identifications even fr

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

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

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

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

195 The false positive rate in 140 patients with laboratory conf

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

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

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

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

200 The false positive rate was 79.8 per 1000 screenings.

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

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

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

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

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

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

207 161 cases (5.6%; 95% CI: 1.0%, 10%), and the false-positive rate for CO-RADS category 5 was one of 28

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

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

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

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

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

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

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

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

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

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

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

219 We find false positive rates of templated mutagenesis in murine

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

235 cellent agreement between the tests and rare false-positive reactivity for all tests.

236 Although false-positive reactivity was identified, its occurrence

237 inations (100 showing cancers, 40 leading to false-positive recalls, 100 normal) were interpreted by

238 r biofluids and substances that can elicit a false-positive response to colorimetric or presumptive t

239 mic, and cosmogenic radiation that may cause false positive responses.

240 No "false positive" responses were obtained from ion chromat

241 had a titer of <1:5, while the sample with a false-positive result (n = 1) yielded a 1+ result.

242 neurodegenerative phenotypes might represent false positives resulting from clocks not robustly calib

243 tected population structure can lead to both false positive results and failures to detect genuine as

244 owever, a main limitation of ARMS-PCR is the false positive results obtained due to nonspecific primi

245 between samples, increases the likelihood of false positive results, and subsequently limits reproduc

246 This phenomenon results in up to 5-10% of false positive results, depending on the chemical librar

247 iate live from dead bacteria eliminating the false positive results.

248 n frequency in future fNIRS studies to avoid false positive results.

249 ill lead to additional endoscopies with some false positive results.

250 The overwhelming proportion of false positives results in reported 'F-Scores' of ~0.3.

251 -negative results (FNRs) of 20% or less, and false-positive results (FPRs) of 20% or less.

252 th digital breast tomosynthesis led to fewer false-positive results and higher specificity but did no

253 r whether the benefits outweigh the risks of false-positive results and overdiagnosis of insignifican

254 s the likelihood of obtaining and publishing false-positive results and overestimated effect sizes.

255 substrates is an underappreciated source of false-positive results and unreproducible behavior.

256 n = 5), and 1:20 (n = 1), while samples with false-positive results by CryptoPS (n = 2) yielded Posit

257 icity for all targets was >=87.2%, with many false-positive results compared to culture that were con

258 esults due to blurring or missing lesions or false-positive results due to pseudo-low-uptake patterns

259 tation of QFT-Plus for the identification of false-positive results in low-risk health care workers.

260 There were no false-positive results in the 710 analyzed subjects.

261 In contrast, false-positive results may fail to identify susceptible

262 improved as a result of screening, and many false-positive results required additional, subsequent M

263 Of note, an increased rate of false-positive results was observed among simulated spec

264 ing of nonviral targets avoided 75% (3/4) of false-positive results without generating false-negative

265 ve attached vitreous at the time of surgery (false-positive results).

266 preted, reviews causes of false-negative and false-positive results, and provides strategies to avoid

267 ith abnormal MS/MS screens, WES could reduce false-positive results, facilitate timely case resolutio

268 use of chest CT there are a large number of false-positive results.

269 ed with DM and led to 2% (four of 159) fewer false-positive results.

270 alysis, while indirect photometry may cause "false positive" results (5% of analyzed samples).

271 ion efficiency with a negligible increase of false-positive risk, it contains several step-by-step op

272 Of the 21 false-positive samples genotyped by PANDAA, only 6 (29%)

273 oth strategies had the most screening tests, false-positive screening results, and benign biopsy resu

274 on/enrichment, and data analysis to suppress false-positive sequences from amplification bias.

275 mple binding, the search would be speeded if false-positive sequences were eliminated from the genome

276 -resolution fluorescence imaging is prone to false positive signals as the detection of protein proxi

277 oor precision for these tasks, yielding many false positive signals.

278 False-positive signals were seen mainly at the prostate

279 quencher-free approach that is resistant to false-positive signals, overcoming limitations associate

280 multiple testing burden and the proneness to false-positive signals.

281 = 70; 66%), unspecified SPs (n = 3, 3%), and false positive SPs (n = 5, 5%).

282 artifacts were miscalled as struts giving 1% false-positive strut detection.

283 be strongly outweighed by factors including false-positive TB treatment, reduced sensitivity, and fo

284 Ten (4.1%) false-positive tears or detachments were identified, wit

285 nemal test are usually considered biological false-positive test results (BFPs), which can be attribu

286 ncrease confidence in HTS data by decreasing false positive testing results.

287 ther Spiromastigoides isolates as a cause of false-positive testing results, their phylogenetic relat

288 more parsimonious set of features with fewer false positives than nCV.

289 accepting both more true positives and fewer false positives than the conventional approach of hidden

290 ng the tail probability of the proportion of false positives (TPPFP) and accounted for correlated tes

291 meropenem (<=32 mm) result in high rates of false positives upon confirmatory testing.

292 organisms present in the sample with minimal false positives using a stepwise convergent solution.

293 able factors are common and may lead to many false positives using alternative methods.

294 n unique molecular identifiers and filtering false positive variant calls caused by amplification of

295 nment bias that limit accuracy, resulting in false positive variant calls.

296 False positives were removed by a phrase pattern and a c

297 For estimation of specificity, false-positives were obtained by assessing for progressi

298 dramatically improve estimates and eliminate false positives when the assumptions of existing methods

299 Of the 11 sera that were false positive with ELISA, seven samples (63.6%) were se

300 e diagnostically specific, i.e., produced no false positives, with the exceptions of 2 ELISAs.