Comparative assessments of objective peak-detection algorithms. II. Studies in men

1988 ◽  
Vol 254 (1) ◽  
pp. E113-E119 ◽  
Author(s):  
R. J. Urban ◽  
D. L. Kaiser ◽  
E. van Cauter ◽  
M. L. Johnson ◽  
J. D. Veldhuis
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Peak Frequency ◽  
Pulse Frequency ◽  
Data Sets ◽  
Empirical Distributions ◽  
Detection Algorithms ◽  
Sampling Intensity ◽  
Positive Rate ◽  
Simulated Series

The performances of eight currently available computerized pulse-detection algorithms were compared on signal-free noise and physiological luteinizing hormone (LH) time series. Signal-free noise was made to vary from 4 to 36% for Gaussian and empirical distributions. Physiological LH data were obtained by immunoassay of blood samples withdrawn every 5 min for 24 h in 8 healthy men, so that the data sets could be emended to simulate varying sampling intensities. Whenever possible, programs were tested at a presumptive 1% false-positive rate. In relation to signal-free noise, the Santen and Bardin program and its modification manifested elevated false-positive rates when the intraseries coefficients of variation increased. The Regional Dual-Threshold program yielded a 1% false-positive rate except on simulated series with high variance. The Cluster and Detect programs both approximated a 1% false-positive rate and the Ultra program approximated a 2.3% false-positive rate throughout the entire range of variance tested. In regard to physiological LH data, all algorithms disclosed a significant impact of sampling intensity on estimates of LH pulse frequency. Sampling-intensity dependent estimates of LH peak frequency by three of the eight programs (Ultra, Cluster, and Detect) were statistically indistinguishable from each other but distinct from the five other programs tested. Furthermore, when judged in relation to their ability to identify individual peaks, the three congruent programs were minimally distinguishable (McNemar's test). Rather, these programs identified the same particular peaks (as defined by concordance of peak maxima) at least 72% of the time.

scholarly journals Excess False Positive Rates in Methods for Differential Gene Expression Analysis using RNA-Seq Data

2015 ◽  
Author(s):  
David M Rocke ◽  
Luyao Ruan ◽  
Yilun Zhang ◽  
J. Jared Gossett ◽  
Blythe Durbin-Johnson ◽  
...  
Keyword(s):  
Linear Model ◽  
False Positive ◽  
Negative Binomial ◽  
False Positive Rate ◽  
Real Data ◽  
False Positives ◽  
P Value ◽  
Data Sets ◽  
Rna Seq ◽  
Positive Rate

Motivation: An important property of a valid method for testing for differential expression is that the false positive rate should at least roughly correspond to the p-value cutoff, so that if 10,000 genes are tested at a p-value cutoff of 10−4, and if all the null hypotheses are true, then there should be only about 1 gene declared to be significantly differentially expressed. We tested this by resampling from existing RNA-Seq data sets and also by matched negative binomial simulations. Results: Methods we examined, which rely strongly on a negative binomial model, such as edgeR, DESeq, and DESeq2, show large numbers of false positives in both the resampled real-data case and in the simulated negative binomial case. This also occurs with a negative binomial generalized linear model function in R. Methods that use only the variance function, such as limma-voom, do not show excessive false positives, as is also the case with a variance stabilizing transformation followed by linear model analysis with limma. The excess false positives are likely caused by apparently small biases in estimation of negative binomial dispersion and, perhaps surprisingly, occur mostly when the mean and/or the dis-persion is high, rather than for low-count genes.

scholarly journals What are steering pictures are worth? Using image-based steering features to detect drowsiness on rural roads

2019 ◽  
Vol 63 (1) ◽  
pp. 2041-2045
Author(s):  
Kartik Mutya ◽  
Jayesh Shah ◽  
Anthony D. McDonald ◽  
Jaycelyn Jefferson
Keyword(s):  
False Positive ◽  
Low Cost ◽  
False Positive Rate ◽  
Steering Wheel ◽  
Recurrence Plots ◽  
Drowsy Driving ◽  
Detection Rates ◽  
Detection Algorithms ◽  
Angle Data ◽  
Positive Rate

Drowsy driving is a persistent and significant problem on today’s roadways. Mitigation technologies may help resolve the problem, but their success depends on effective detection algorithms. Steering-based algorithms are a promising direction for such effective algorithms because of their low cost and ease of implementation. However, steering-based approaches are often limited by high false positive detection rates. The goal of this study was to assess if image-based steering features and convolutional neural networks can reduce these high false positive rates. The analysis investigated two methods for transforming steering wheel angle data into images, Markov Transition Field and recurrence plots. Area under the ROC curve and false positive rate results suggest that both approaches nominally improve detection performance and reduce false positives relative to a benchmark, with some evidence that recurrence plots have the highest performance.

Estimating false-positive and false-negative errors in analyses of hormonal pulsatility

1988 ◽  
Vol 254 (6) ◽  
pp. E786-E794 ◽  
Author(s):  
E. Van Cauter
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
False Negative ◽  
Pulse Frequency ◽  
Computer Algorithms ◽  
Pulse Detection ◽  
Negative Error ◽  
False Negative Error ◽  
Positive Rate ◽  
In Series

Previous studies evaluating computer algorithms for endocrine pulse detection have estimated the rate of false-positive pulses in series of purely random variations (i.e., “noise”) and have determined pulse-detection criteria associated with low levels of such false-positive rates. The present study investigates the relationship between the false-positive rate and the sizes of the false-positive and false-negative errors on pulse frequency for series including both pulses and noise. The algorithm used (ULTRA) proceeds by eliminating all peaks of concentration for which either the increment or the decrement does not exceed a threshold expressed in multiples of the local intra-assay coefficient of variation. A total of 336 computer-generated series was analyzed using thresholds of two and three coefficients of variation. The effects of noise level, pulse frequency, pulse amplitude, and presence of a base-line variation on the sizes of the false-positive and false-negative errors were evaluated. The false-positive rate in noise series exceeded the false-positive rate by a 4- to 10-fold factor in series including at least 8 pulses/100 samples. When pulse frequency increased, the false-positive error decreased, but the false-negative error increased. In series with more than 8 pulses/100 samples, the use of thresholds aimed at maintaining the false-positive rate in noise series below 1% resulted in a false-negative error in excess of 20%. In conclusion, for hormonal profiles that include 8 or more pulses/100 samples, the use of pulse-detection criteria tailored to minimize the false-positive rate in noise series may result in an underestimation of pulse frequency.

scholarly journals A bootstrap approach is a superior statistical method for the comparison of cell-to-cell movement data

2020 ◽  
Author(s):  
Matthew G. Johnston ◽  
Christine Faulkner
Keyword(s):  
False Positive ◽  
Bootstrap Method ◽  
False Positive Rate ◽  
Cell Movement ◽  
Wilcoxon Test ◽  
Data Sets ◽  
Movement Data ◽  
Positive Rate ◽  
Intercellular Movement ◽  
The Bootstrap Method

SummaryPlasmodesmata are an increasing focus of plant research, and plant physiologists frequently aim to understand the dynamics of intercellular movement and plasmodesmal function. For this, experiments that measure the spread of GFP between cells are commonly performed to indicate whether plasmodesmata are more open or closed in different conditions or in different genotypes.We propose cell-to-cell movement data sets are better analysed by a bootstrap method that tests the null hypothesis that means (or medians) are the same between two conditions, instead of the commonly used Mann-Whitney-Wilcoxon test. We found that that with hypothetical distributions similar to cell-to-cell movement data, the Mann-Whitney-Wilcoxon produces a false positive rate of 17% while the bootstrap method maintains a false positive at the set rate of 5% under the same circumstances. Here we present this finding, as well as our rationale, an explanation of the bootstrap method and an R script for easy use. We have further demonstrated its use on published datasets from independent laboratories.

Improving diagnosis of acute appendicitis with atypical findings by Tc-99m HMPAO leukocyte scan

2002 ◽  
Vol 41 (01) ◽  
pp. 37-41 ◽  
Author(s):  
S. Shung-Shung ◽  
S. Yu-Chien ◽  
Y. Mei-Due ◽  
W. Hwei-Chung ◽  
A. Kao
Keyword(s):  
Acute Appendicitis ◽  
False Positive ◽  
False Positive Rate ◽  
Accurate Method ◽  
Clinical Findings ◽  
Pathological Findings ◽  
Lower Quadrant ◽  
Predictive Values ◽  
Positive Rate

Summary Aim: Even with careful observation, the overall false-positive rate of laparotomy remains 10-15% when acute appendicitis was suspected. Therefore, the clinical efficacy of Tc-99m HMPAO labeled leukocyte (TC-WBC) scan for the diagnosis of acute appendicitis in patients presenting with atypical clinical findings is assessed. Patients and Methods: Eighty patients presenting with acute abdominal pain and possible acute appendicitis but atypical findings were included in this study. After intravenous injection of TC-WBC, serial anterior abdominal/pelvic images at 30, 60, 120 and 240 min with 800k counts were obtained with a gamma camera. Any abnormal localization of radioactivity in the right lower quadrant of the abdomen, equal to or greater than bone marrow activity, was considered as a positive scan. Results: 36 out of 49 patients showing positive TC-WBC scans received appendectomy. They all proved to have positive pathological findings. Five positive TC-WBC were not related to acute appendicitis, because of other pathological lesions. Eight patients were not operated and clinical follow-up after one month revealed no acute abdominal condition. Three of 31 patients with negative TC-WBC scans received appendectomy. They also presented positive pathological findings. The remaining 28 patients did not receive operations and revealed no evidence of appendicitis after at least one month of follow-up. The overall sensitivity, specificity, accuracy, positive and negative predictive values for TC-WBC scan to diagnose acute appendicitis were 92, 78, 86, 82, and 90%, respectively. Conclusion: TC-WBC scan provides a rapid and highly accurate method for the diagnosis of acute appendicitis in patients with equivocal clinical examination. It proved useful in reducing the false-positive rate of laparotomy and shortens the time necessary for clinical observation.

Predicting Fetal Chromosome Anomalies in the First Trimester Using Pregnancy Associated Plasma Protein-A: A Comparison of Statistical Methods

1993 ◽  
Vol 32 (02) ◽  
pp. 175-179 ◽  
Author(s):  
B. Brambati ◽  
T. Chard ◽  
J. G. Grudzinskas ◽  
M. C. M. Macintosh
Keyword(s):  
Logistic Regression ◽  
General Population ◽  
Likelihood Ratio ◽  
False Positive ◽  
False Positive Rate ◽  
Ratio Method ◽  
Detection Rates ◽  
Gaussian Distributions ◽  
Positive Rate ◽  
Likelihood Ratio Method

Abstract:The analysis of the clinical efficiency of a biochemical parameter in the prediction of chromosome anomalies is described, using a database of 475 cases including 30 abnormalities. A comparison was made of two different approaches to the statistical analysis: the use of Gaussian frequency distributions and likelihood ratios, and logistic regression. Both methods computed that for a 5% false-positive rate approximately 60% of anomalies are detected on the basis of maternal age and serum PAPP-A. The logistic regression analysis is appropriate where the outcome variable (chromosome anomaly) is binary and the detection rates refer to the original data only. The likelihood ratio method is used to predict the outcome in the general population. The latter method depends on the data or some transformation of the data fitting a known frequency distribution (Gaussian in this case). The precision of the predicted detection rates is limited by the small sample of abnormals (30 cases). Varying the means and standard deviations (to the limits of their 95% confidence intervals) of the fitted log Gaussian distributions resulted in a detection rate varying between 42% and 79% for a 5% false-positive rate. Thus, although the likelihood ratio method is potentially the better method in determining the usefulness of a test in the general population, larger numbers of abnormal cases are required to stabilise the means and standard deviations of the fitted log Gaussian distributions.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

scholarly journals PRATD: A Phased Remote Access Trojan Detection Method with Double-Sided Features

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1894
Author(s):  
Chun Guo ◽  
Zihua Song ◽  
Yuan Ping ◽  
Guowei Shen ◽  
Yuhei Cui ◽  
...  
Keyword(s):  
False Positive ◽  
Detection Method ◽  
False Positive Rate ◽  
True Positive Rate ◽  
Remote Access ◽  
Detection Methods ◽  
Security Threats ◽  
True Positive ◽  
Trojan Detection ◽  
Positive Rate

Remote Access Trojan (RAT) is one of the most terrible security threats that organizations face today. At present, two major RAT detection methods are host-based and network-based detection methods. To complement one another’s strengths, this article proposes a phased RATs detection method by combining double-side features (PRATD). In PRATD, both host-side and network-side features are combined to build detection models, which is conducive to distinguishing the RATs from benign programs because that the RATs not only generate traffic on the network but also leave traces on the host at run time. Besides, PRATD trains two different detection models for the two runtime states of RATs for improving the True Positive Rate (TPR). The experiments on the network and host records collected from five kinds of benign programs and 20 famous RATs show that PRATD can effectively detect RATs, it can achieve a TPR as high as 93.609% with a False Positive Rate (FPR) as low as 0.407% for the known RATs, a TPR 81.928% and FPR 0.185% for the unknown RATs, which suggests it is a competitive candidate for RAT detection.

Evidence for Age-Adjusted D-Dimer to Rule out Pulmonary Embolism: An Institutional Study

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S5-S5
Author(s):  
Ridin Balakrishnan ◽  
Daniel Casa ◽  
Morayma Reyes Gil
Keyword(s):  
Pulmonary Embolism ◽  
False Positive ◽  
False Positive Rate ◽  
Moderate Risk ◽  
Older Population ◽  
Statistical Measures ◽  
Positive Rate ◽  
Risk Patients ◽  
D Dimer ◽  
Rule Out

Abstract The diagnostic approach for ruling out suspected acute pulmonary embolism (PE) in the ED setting includes several tests: ultrasound, plasma d-dimer assays, ventilation-perfusion scans and computed tomography pulmonary angiography (CTPA). Importantly, a pretest probability scoring algorithm is highly recommended to triage high risk cases while also preventing unnecessary testing and harm to low/moderate risk patients. The d-dimer assay (both ELISA and immunoturbidometric) has been shown to be extremely sensitive to rule out PE in conjunction with clinical probability. In particularly, d-dimer testing is recommended for low/moderate risk patients, in whom a negative d-dimer essentially rules out PE sparing these patients from CTPA radiation exposure, longer hospital stay and anticoagulation. However, an unspecific increase in fibrin-degradation related products has been seen with increase in age, resulting in higher false positive rate in the older population. This study analyzed patient visits to the ED of a large academic institution for five years and looked at the relationship between d-dimer values, age and CTPA results to better understand the value of age-adjusted d-dimer cut-offs in ruling out PE in the older population. A total of 7660 ED visits had a CTPA done to rule out PE; out of which 1875 cases had a d-dimer done in conjunction with the CT and 5875 had only CTPA done. Out of the 1875 cases, 1591 had positive d-dimer results (>0.50 µg/ml (FEU)), of which 910 (57%) were from patients older than or equal to fifty years of age. In these older patients, 779 (86%) had a negative CT result. The following were the statistical measures of the d-dimer test before adjusting for age: sensitivity (98%), specificity (12%); negative predictive value (98%) and false positive rate (88%). After adjusting for age in people older than 50 years (d-dimer cut off = age/100), 138 patients eventually turned out to be d-dimer negative and every case but four had a CT result that was also negative for a PE. The four cases included two non-diagnostic results and two with subacute/chronic/subsegmental PE on imaging. None of these four patients were prescribed anticoagulation. The statistical measures of the d-dimer test after adjusting for age showed: sensitivity (96%), specificity (20%); negative predictive value (98%) and a decrease in the false positive rate (80%). Therefore, imaging could have been potentially avoided in 138/779 (18%) of the patients who were part of this older population and had eventual negative or not clinically significant findings on CTPA if age-adjusted d-dimers were used. This data very strongly advocates for the clinical usefulness of an age-adjusted cut-off of d-dimer to rule out PE.

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