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We assessed two electronic search tools that screen medical records for documented fractures. Both programs reliably identified patients with any fracture but missed individuals with minimal trauma fracture to different degrees. A hybrid tool combining the methodology of both tools is likely to improve the identification of those with osteoporosis. Most patients who suffer a minimal trauma fracture remain undiagnosed, placing them at high risk of refracture. Case finding can be improved by electronic search tools that screen medical records for documented fractures. Here, we assessed the efficacy of two new programs, AES and XRAIT, in identifying patients with minimal trauma fracture. Each tool was applied to search the electronic medical record and/or radiology reports at two tertiary hospitals in Sydney, Australia, from 1 July to 31 December 2018. Samples of the extracted reports were then manually reviewed to determine the sensitivity of each program in detecting minimal trauma fractures. At the two centers, AES detected 872 and 1364 cases, whereas XRAIT identified 1414 and 2180 patients with fractures, respectively. The true positive rate for “any fracture” was similar for both instruments (77–88%). However, the ability to detect “minimal trauma fractures” differed between programs and centers (53–75% accuracy), with each tool identifying separate subsets of patients. Concordance between both tools was less than half of the combined total number of minimal trauma fractures (43–45%). Considering the total number of minimal trauma fractures detected by both tools combined, AES correctly identified 52–55% of cases while XRAIT identified 88–93% of cases. Both programs reliably identified patients with any fracture but missed individuals with minimal trauma fracture to different degrees. Hybrid tools combining the methodology of XRAIT and AES are likely to improve the identification of patients who require investigation and treatment for osteoporosis.

Objective To analyze the association between radiologists’ performance and image position within a batch in screen reading of mammograms in Norway. Method We described true and false positives and true and false negatives by groups of image positions and batch sizes for 2,937,312 screen readings performed from 2012 to 2018. Mixed-effects models were used to obtain adjusted proportions of true and false positive, true and false negative, sensitivity, and specificity for different image positions. We adjusted for time of day and weekday and included the individual variation between the radiologists as random effects. Time spent reading was included in an additional model to explore a possible mediation effect. Result True and false positives were negatively associated with image position within the batch, while the rates of true and false negatives were positively associated. In the adjusted analyses, the rate of true positives was 4.0 per 1000 (95% CI: 3.8–4.2) readings for image position 10 and 3.9 (95% CI: 3.7–4.1) for image position 60. The rate of true negatives was 94.4% (95% CI: 94.0–94.8) for image position 10 and 94.8% (95% CI: 94.4–95.2) for image position 60. Per 1000 readings, the rate of false negative was 0.60 (95% CI: 0.53–0.67) for image position 10 and 0.62 (95% CI: 0.55–0.69) for image position 60. Conclusion There was a decrease in the radiologists’ sensitivity throughout the batch, and although this effect was small, our results may be clinically relevant at a population level or when multiplying the differences with the number of screen readings for the individual radiologists. Key Points • True and false positive reading scores were negatively associated with image position within a batch. • A decreasing trend of positive scores indicated a beneficial effect of a certain number of screen readings within a batch. • False negative scores increased throughout the batch but the association was not statistically significant.

High-resolution mass spectrometry (HRMS) enables rapid chemical annotation via accurate mass measurements and matching of experimentally derived spectra with reference spectra. Reference libraries are generated from chemical standards and are therefore limited in size relative to known chemical space. To address this limitation, in silico spectra (i.e., MS/MS or MS2 spectra), predicted via Competitive Fragmentation Modeling-ID (CFM-ID) algorithms, were generated for compounds within the U.S. Environmental Protection Agency’s (EPA) Distributed Structure-Searchable Toxicity (DSSTox) database (totaling, at the time of analysis, ~ 765,000 substances). Experimental spectra from EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT) mixtures (n = 10) were then used to evaluate the performance of the in silico spectra. Overall, MS2 spectra were acquired for 377 unique compounds from the ENTACT mixtures. Approximately 53% of these compounds were correctly identified using a commercial reference library, whereas up to 50% were correctly identified as the top hit using the in silico library. Together, the reference and in silico libraries were able to correctly identify 73% of the 377 ENTACT substances. When using the in silico spectra for candidate filtering, an examination of binary classifiers showed a true positive rate (TPR) of 0.90 associated with false positive rates (FPRs) of 0.10 to 0.85, depending on the sample and method of candidate filtering. Taken together, these findings show the abilities of in silico spectra to correctly identify true positives in complex samples (at rates comparable to those observed with reference spectra), and efficiently filter large numbers of potential false positives from further consideration. Graphical abstract Electronic supplementary material The online version of this article (10.1007/s00216-019-02351-7) contains supplementary material, which is available to authorized users.

A Bloom filter is a special case of an artificial neural network with two layers. Traditionally, it is seen as a simple data structure supporting membership queries on a set. The standard Bloom filter does not support the delete operation, and therefore, many applications use a counting Bloom filter to enable deletion. This paper proposes a generalization of the counting Bloom filter approach, called “autoscaling Bloom filters”, which allows adjustment of its capacity with probabilistic bounds on false positives and true positives. Thus, by relaxing the requirement on perfect true positive rate, the proposed autoscaling Bloom filter addresses the major difficulty of Bloom filters with respect to their scalability. In essence, the autoscaling Bloom filter is a binarized counting Bloom filter with an adjustable binarization threshold. We present the mathematical analysis of its performance and provide a procedure for minimizing its false positive rate., Neural Computing and Applications, 32 (8), ISSN:1433-3058, ISSN:0941-0643

How accurately can all recorded locations of 97 knife homicides in one year be forecast across all 4835 Lower Layer Super Output Areas (LSOAs) of London, based only upon all 3506 known locations of nonfatal knife injury assaults in the preceding year? All recorded “knife crimes” in the Metropolitan Police Service (MPS) area of London in the financial year 2016–2017 (year 1) were manually reviewed to identify all 3506 reported locations of knife-enabled (KE) but nonfatal injuries, as distinct from other events digitally coded as “knife crimes”, such as displaying, threatening with, or carrying knives. All KE homicides in 2017–2018 (year 2) were then added to the database. Each KE injury assault in year 1 was classified for occurrence in one of London’s 4835 LSOAs. The total N of such crimes within each LSOA was summed across all records to divide all LSOAs into seven categories of frequency of KE injury assaults in 2016/2017: 0, 1, 2, 3, 4, 5, and 6 or more. We then divided the N of LSOAs in each category in 2016/2017 (year 1) into the total N of knife homicides in 2017/2018 (year 2). False positives, false negatives, and percentage of homicides targeted were calculated for six different targeting plans. Over two thirds (69%) of KE homicides in 2017/2018 (year 2) occurred in just 67 (1.4%) of all 4835 LSOAs, comprising 3.3% of the 2048 LSOAs that had had one or more of the 3506 KE injury assaults mapped in 2016/2017 (year 1). The proportion of LSOAS with a KE homicide in year 2 was higher where there were higher numbers of KE injury assaults per LSOA in year 1. Among LSOAs with zero assaults in year 1, only 1% had a KE homicide in year 2. Among LSOAs with six or more KE injury assaults in year 1, 15% had a KE homicide in year 2. While the risk of homicide was 1400% higher in the hottest spots of knife assaults than in the coolest spots, the absolute number of year two KE homicides in those hottest areas was only 6% of the total. All LSOAs with one or more year 1 KE assaults had three times as much KE homicide risk than LSOAs with no year 1 KE assaults. Targeting all 2048 areas that had one or more year 1 KE assaults would have yielded a true positive rate of over 3% and covered 69% of actual homicide locations. The true negative rate for 2781 areas that would not have been targeted based on having no year 1 KE injuries would have been 99%. Predicting which local areas are most likely to suffer knife-enabled homicides, based only on recent nonfatal knife injuries, can pinpoint risks of homicide in local areas that are up to 1400% higher than in most local areas, offering a range of strategies for resource allocation.

The Iowa Newborn Screening (NBS) Program began screening for very long-chain acyl-CoA dehydrogenase deficiency (VLCAD) in 2003. Untreated VLCAD can lead to liver failure, heart failure, and death. Current confirmatory testing recommendations by the American College of Medical Genetics (ACMG) for VLCAD list molecular and functional analysis (i.e., fibroblast fatty acid oxidation probe) as optional. This can lead to misclassification of VLCAD carriers as false positives. Iowa implemented a comprehensive VLCAD confirmatory testing algorithm at the beginning of 2016 that included both molecular and fibroblast analysis. Here, we compare the historic multi-algorithmic confirmatory testing protocol (2005–2016) to this comprehensive protocol (2016–2017). A metabolic specialist reviewed all medical records and NBS data for each out-of-range VLCAD that fell in each testing period. During the comprehensive testing period, 48,651 specimens were screened. Thirteen individuals with out-of-range C14:1 results were classified as follows after review: ten carriers, zero true positives, zero false positives, zero lost to follow-up, and four unable to assess carrier status. During the variable testing period, a total of 486,566 specimens were screened. Eighty-five individuals with out-of-range C14:1 were classified as follows: 45 carriers, two true positives, four false positives, four lost to follow-up, and 30 unable to assess carrier status. Our findings suggest that many out-of-range VLCAD cases that do not receive molecular confirmatory testing could be carriers mistakenly classified as false positives. We recommend comprehensive molecular and functional testing for all children with out-of-range VLCAD NBS results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12687-019-00409-8) contains supplementary material, which is available to authorized users.

Funder: University of Cambridge, Research question How accurately can all locations of 44 fatal collisions in 1 year be forecasted across 1403 micro-areas in Toronto, based upon locations of all 1482 non-fatal collisions in the preceding 4 years? Data All 1482 non-fatal traffic collisions from 2008 through 2011 and all 44 fatal traffic collisions in 2012 in the City of Toronto, Ontario, were geocoded from public records to 1403 micro-areas called ‘hexagonal tessellations’. Methods The total number of non-fatal traffic collisions in Period 1 (2008 through 2011) was summed within each micro-area. The areas were then classified into seven categories of frequency of non-fatal collisions: 0, 1, 2, 3, 4, 5, and 6 or more. We then divided the number of micro-areas in each category in Period 1 into the total number of fatal traffic collisions in each category in Period 2 (2012). The sensitivity and specificity of forecasting fatal collision risk based on prior non-fatal collisions were then calculated for five different targeting strategies. Findings The micro-locations of 70.5% of fatal collisions in Period 2 had experienced at least 1 non-fatal collision in Period 1. In micro-areas that had zero non-fatal collisions during Period 1, only 1.7% had a fatal collision in Period 2. Across all areas, the probability of a fatal collision in the area during Period 2 increased with the number of non-fatal collisions in Period 1, with 6 or more non-fatal collisions in Period 1 yielding a risk of fatal collision in Period 2 that was 8.7 times higher than in areas with no non-fatal collisions. This pattern is evidence that targeting 25% of micro-areas effectively could cut total traffic fatalities in a given year by up to 50%. Conclusion Highly elevated risks of traffic fatalities can be forecasted based on prior non-fatal collisions, targeting a smaller portion of the city for more concentrated investment in saving lives.

While speaking, humans exhibit a number of recognizable patterns; most notably, the repetitive nature of mouth movement from closed to open. The following paper presents a novel method to computationally determine when video data contains a person speaking through the recognition and tally of lip facial closures within a given interval. A combination of Haar-Feature detection and eigenvectors are used to recognize when a target individual is present, but by detecting and quantifying spasmodic lip movements and comparing them to the ranges seen in true positives, we are able to predict when true speech occurs without the need for complex facial mappings. Although the results are within a reasonable accuracy range when compared to current methods, the comprehensibility and simple nature of the approach used can reduce the strenuousness of current techniques and, if paired with synchronous audio recognition methods, can streamline the future of voice activity detection as a whole.

The introduction of dedicated phlebotomy teams certified for blood collection has been reported to be highly cost-effective by reducing contamination rates. However, data on their effects on blood volume and true positive rate are limited. Therefore, we investigated the effect of replacing interns with a phlebotomy team on blood culture results. We performed a 24-month retrospective, quasi-experimental study before and after the introduction of a phlebotomy team dedicated to collecting blood cultures in a 2700-bed tertiary-care hospital. The microbiology laboratory database was used to identify adult patients with positive blood culture results. During the study period, there were no changes in blood collection method, blood culture tubes, and the application of antiseptic measures. Blood volume was measured by the BACTEC™ FX system based on red blood cell metabolism. A total of 162,207 blood cultures from 23,563 patients were analyzed, comprising 78,673 blood cultures during the intern period and 83,534 during the phlebotomy team period. Blood volume increased from a mean of 2.1 ml in the intern period to a mean of 5.6 ml in the phlebotomy team period (p

An intrusion prevention system (IPS) acts as a new type of information security technology, the configuration and management of which are currently urgent problems; in particular, debate exists regarding the value of these systems. In this paper, we analyse whether a firm realizes a positive or negative value from using an IPS instead of an intrusion detection system (IDS) in a default configuration and an optimal configuration, respectively. Our results suggest: (a) an IPS could hurt the firm when not configured optimally; (b) the optimal configuration of the IPS depends not only on the cost parameters but also on the external environment (quality of the IDS) in which the firm is operating; (c) whether the IDS is optimally configured or not, the firm will make the same decisions between using the IPS instead of the IDS and continuing to use the IDS; and (d) except for the true positive rate of IDS being in a certain region and the blocking cost being sufficiently high, the firm realizes a strictly nonnegative value if the firm configures the IPS optimally.

Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.

Hand, foot and mouth disease (HFMD) is a serious public health problem, and coxsackievirus A6 (CVA6) and coxsackievirus A10 (CVA10) are two of the major causative pathogens, in addition to enterovirus 71 (EV71) and coxsackievirus A16 (CVA16). A simple and rapid reverse transcription recombinase-aided amplification assay (RT-RAA) was developed for the detection of CVA10 and CVA6 in this study. The analytical sensitivity for detection of CVA10 and CVA6 at 95% probability by probit regression analysis was 35 copies per reaction and 38 copies per reaction, respectively, with 100% specificity. Compared with commercial RT-qPCR assays, when testing 455 fecal specimens, the kappa value of the RT-RAA assay for CVA10 and CVA6 was 0.920 (p < 0.001) and 0.952 (p < 0.001), respectively. Moreover, four samples that were positive for CVA10 and five that were positive for CVA6 by RT-RAA but negative by RT-qPCR were further determined to be true positives. These results demonstrate that the proposed RT-RAA assays are very valuable tools for the detection of CVA10 and CVA6 and have potential for use in resource-limited settings.

The existing anti-phishing approaches use the blacklist methods or features based machine learning techniques. Blacklist methods fail to detect new phishing attacks and produce high false positive rate. Moreover, existing machine learning based methods extract features from the third party, search engine, etc. Therefore, they are complicated, slow in nature, and not fit for the real-time environment. To solve this problem, this paper presents a machine learning based novel anti-phishing approach that extracts the features from client side only. We have examined the various attributes of the phishing and legitimate websites in depth and identified nineteen outstanding features to distinguish phishing websites from legitimate ones. These nineteen features are extracted from the URL and source code of the website and do not depend on any third party, which makes the proposed approach fast, reliable, and intelligent. Compared to other methods, the proposed approach has relatively high accuracy in detection of phishing websites as it achieved 99.39% true positive rate and 99.09% of overall detection accuracy.

Basic health and infection control measures are the main methods of protection against COVID-19. Patients are well informed about how practitioners should be conducting themselves, however, they may lose trust in clinicians who fail to demonstrate, and promote those same basic prevention measures. The broader COVID-19 strategy has included the rapid development and deployment of swabs and antibody tests. Flaws in testing fail to offer assurances due to false negatives while even true positives cannot guarantee future immunity as there is uncertainty regarding long-term antibody response. An understanding of human factors and an appreciation of the limitations of available tests could offer healthcare staff mechanisms to encourage safety.

Drivable ground detection contributes to the perfect navigation of unmanned vehicle systems, and this significantly attracted the attention of researchers. Various vision-based techniques have been proposed, and amazing results are accomplished towards drivable ground detection. Despite these achievements, environmental noises like snows, rains and shadows have an effect that can lead to mis-detection of drivable ground. After conducting a brief study on snow, rain and shadow, we introduce filtering algorithms into the drivable ground detection system to overcome the effect of these environmental noises. Experimental comparison was carried out qualitatively and quantitatively. Quantitative experiments were carried out using these following schemes: accuracy rate (ACC), error rate (ERR), true positive rate (TPR), false negative rate (FNR), true negative rate (TNR), false positive rate (FPR) and precision (PRE). These schemes are used for a comparison between the system with and without a filtering algorithm. The results from all experiments show improved performance of the system with a filtering algorithm over other systems, and these massively contributed to perfect navigation for the unmanned vehicle system.

Screening for critical congenital heart disease (CCHD) using pulse oximetry has been endorsed by the American Academy of Pediatrics and the American Heart Association. The recommended screening requires two saturation readings. We sought to determine the incidence of undetected CCHD in Tennessee for the 2 years following implementation of an algorithm that assigned an immediate pass to a single lower extremity saturation of 97% or higher. State Genetic Screening records and reports of missed cases from the Tennessee Initiative for Perinatal Quality Care were used to determine if CCHD cases were missed by the new screening algorithm. During the study, 232 infants failed the screen with 51 or 22% true positives, 13 infants had undetected CCHD (10 coarctations, 2 anomalous veins and 1 Tetralogy of Fallot). This approach eliminated over 150 000 pulse oximetry determinations in Tennessee without affecting the ability of pulse oximetry to detect CCHD before discharge.

Drug repositioning, the process of discovering, validating, and marketing previously approved drugs for new indications, is of growing interest to academia and industry due to reduced time and costs associated with repositioned drugs. Computational methods for repositioning are appealing because they putatively nominate the most promising candidate drugs for a given indication. Comparing the wide array of computational repositioning methods, however, is a challenge due to inconsistencies in method validation in the field. Furthermore, a common simplifying assumption, that all novel predictions are false, is intellectually unsatisfying and hinders reproducibility. We address this assumption by providing a gold standard database, repoDB, that consists of both true positives (approved drugs), and true negatives (failed drugs). We have made the full database and all code used to prepare it publicly available, and have developed a web application that allows users to browse subsets of the data (http://apps.chiragjpgroup.org/repoDB/).

The study of virus integrations in human genome is important since virus integrations were shown to be associated with diseases. In the literature, few methods have been proposed that predict virus integrations using next generation sequencing datasets. Although they work, they are slow and are not very sensitive. This paper introduces a new method BatVI to predict viral integrations. Our method uses a fast screening method to filter out chimeric reads containing possible viral integrations. Next, sensitive alignments of these candidate chimeric reads are called by BLAST. Chimeric reads that are co-localized in the human genome are clustered. Finally, by assembling the chimeric reads in each cluster, high confident virus integration sites are extracted. We compared the performance of BatVI with existing methods VirusFinder and VirusSeq using both simulated and real-life datasets of liver cancer patients. BatVI ran an order of magnitude faster and was able to predict almost twice the number of true positives compared to other methods while maintaining a false positive rate less than 1%. For the liver cancer datasets, BatVI uncovered novel integrations to two important genes TERT and MLL4, which were missed by previous studies. Through gene expression data, we verified the correctness of these additional integrations. BatVI can be downloaded from http://biogpu.ddns.comp.nus.edu.sg/~ksung/batvi/index.html .

The concentration detection threshold (CDT) is the concentration of particles in solution beyond which a (serial dilution) assay detects particle presence. By our account, CDTs typically are not estimated but are fixed at some value. Setting a CDT to zero ( $$d=0$$ ) implies perfect detection, a common assumption, and setting $$d>0$$ gives results that are “denominated” in units of $$d$$ , i.e., are relative to the choice of $$d$$ . Using multiple, different serial dilution assays, each with its own CDT, we choose a “reference assay,” to which we assign a fixed CDT value, to obtain relative estimates of the remaining assays’ CDTs and the underlying particle concentration. We present the CDTs as a novel way to account for or to compare different serial dilution assays, “sensitivities”. We apply our methodology to data from four assays of the presence of bacterial (B. abortus) antibodies in the serum of elk in the Greater Yellowstone Ecosystem, where transmission of brucellosis—the disease ensuing from infection—to commercial livestock is managed by the Wyoming Game and Fish Department to avoid the primary symptom of abnormal fetal abortion. Results agree qualitatively with the more traditional notion of sensitivity as the true positive rate.

The relative operating characteristic (ROC) is a widely-used method to measure diagnostic signals including predictions of land changes, species distributions, and ecological niches. The ROC measures the degree to which presence for a Boolean variable is associated with high ranks of an index. The ROC curve plots the rate of true positives versus the rate of false positives obtained from the comparison between the Boolean variable and multiple diagnoses derived from thresholds applied to the index. The area under the ROC curve (AUC) is a summary metric, which is commonly reported and frequently criticized. Our manuscript recommends four improvements in the use and interpretation of the ROC curve and its AUC by: (1) highlighting important threshold points on the ROC curve, (2) interpreting the shape of the ROC curve, (3) defining lower and upper bounds for the AUC, and (4) mapping the density of the presence within each bin of the ROC curve. These recommendations encourage scientists to interpret the rich information that the ROC curve can reveal, in a manner that goes far beyond the potentially misleading AUC. We illustrate the benefit of our recommendations by assessing the prediction of land change in a suburban landscape.

Objective:To determine whether novices can distinguish between properly and improperly placed guidewires in a vascular access model after only minimal training.Methods:This was a prospective study involving trainees with no previous training in sonographic guidewire visualization. A vascular access model was created with guidewires positioned inside or adjacent to simulated veins. Subjects were taught to scan each wire to determine its location. Afterward, participants scanned a test model of five vein-wire pairs and recorded their answers as “inside,” “outside,” or “unsure.” The test characteristics of sonographic guidewire localization were determined using actual wire location as the criterion standard.Results:Forty trainees (21 emergency medicine residents, 19 medical students) participated, and each examined five simulated veins. There were 156 true positives (intravascular wire correctly identified), 38 true negatives (extravascular wire correctly identified), 2 false negatives, 2 false positives, and 2 cases in which the participant marked “not sure,” which were reclassified as false negatives. Test characteristics were sensitivity 97.5% (95% CI 93.3–99.2) and specificity 95.0% (95% CI 81.8–99.1). The overall accuracy was 97.0%.Conclusions:Sonographic guidewire visualization, a step recommended for ensuring proper vessel cannulation during central venous access, can be accomplished by novices with a high degree of accuracy.

Factor analysis is an established technique for the detection of measurement bias. Multigroup factor analysis (MGFA) can detect both uniform and nonuniform bias. Restricted factor analysis (RFA) can also be used to detect measurement bias, albeit only uniform measurement bias. Latent moderated structural equations (LMS) enable the estimation of nonlinear interaction effects in structural equation modelling. By extending the RFA method with LMS, the RFA method should be suited to detect nonuniform bias as well as uniform bias. In a simulation study, the RFA/LMS method and the MGFA method are compared in detecting uniform and nonuniform measurement bias under various conditions, varying the size of uniform bias, the size of nonuniform bias, the sample size, and the ability distribution. For each condition, 100 sets of data were generated and analysed through both detection methods. The RFA/LMS and MGFA methods turned out to perform equally well. Percentages of correctly identified items as biased (true positives) generally varied between 92% and 100%, except in small sample size conditions in which the bias was nonuniform and small. For both methods, the percentages of false positives were generally higher than the nominal levels of significance.KeywordsMeasurement bias Differential item functioning Nonlinear structural equation modelling Factor analysis Latent moderated structures

The Dendritic Cell Algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation which results in a 'context aware' detection system. Previous applications of the DCA have included the detection of potentially malicious port scanning activity, where it has produced high rates of true positives and low rates of false positives. In this work we aim to compare the performance of the DCA and of a Self-Organizing Map (SOM) when applied to the detection of SYN port scans, through experimental analysis. A SOM is an ideal candidate for comparison as it shares similarities with the DCA in terms of the data fusion method employed. It is shown that the results of the two systems are comparable, and both produce false positives for the same processes. This shows that the DCA can produce anomaly detection results to the same standard as an established technique., 38 pages, 29 figures, 10 tables, Evolutionary Intelligence

This paper presents a novel bootstrap based method for Receiver Operating Characteristic (ROC) analysis of Fisher classifier. By defining Fisher classifier’s output as a statistic, the bootstrap technique is used to obtain the sampling distributions of the outputs for the positive class and the negative class respectively. As a result, the ROC curve is a plot of all the (False Positive Rate (FPR), True Positive Rate (TPR)) pairs by varying the decision threshold over the whole range of the bootstrap sampling distributions. The advantage of this method is, the bootstrap based ROC curves are much stable than those of the holdout or cross-validation, indicating a more stable ROC analysis of Fisher classifier. Experiments on five data sets publicly available demonstrate the effectiveness of the proposed method.

In early stage drug discovery screens, the efficacy of a potential drug candidate in an in vivo assay is often judged, rather informally, on the proportion of animals that respond to the drug. Only if at least a prespecified proportion of animals respond is the drug considered active enough for further testing. This is a “simple screening strategy.” Researchers are often unaware of the properties of such strategies and what effects changing the parameters of the strategy, such as the sample size, could have. It is suggested and demonstrated here that the properties of a simple screening strategy can be easily understood by considering its true and false positive rates.

The technique of differential display reverse transcription-polymerase chain reaction (ddRT-PCR) has been used to produce unique profiles of up-regulated and down-regulated gene expression in the liver of male Wistar rats following short term exposure to the non-genotoxic hepatocarcinogens, phenobarbital and WY-14,643. Animals were treated for 3 days, whereupon their livers were extracted and snap frozen. mRNA was prepared from the livers and used for ddRT-PCR. Individual bands from the differential displays were extracted and cloned. False positives were eliminated by dotblot screening and true positives then sequenced and identified.

The inter- and intrapatient variability in cyclosporin pharmacokinetics obfuscates the relationship between therapeutic outcome and administered dose. We defined patients with high pharmacokinetic variability and an increased risk of chronic rejection by means of serial pharmacokinetic profiling of 204 renal transplant patients treated for up to 5 years with cyclosporin doses selected to achieve a target average cyclosporin concentration (Cav). Patients were stratified into cohorts according to high versus low pharmacokinetic variability, which was based on the cut-off values of percentage coefficient of variation (%CV) of the dose-corrected Cav (Cav/mg; 35%) or 0-hour concentration (C0/mg; 53%). These values are the inflection points of curves that express the relationships between true positives (patients with high %CV and chronic rejection) versus false positives (patients with high %CV but no evidence of chronic rejection).

The sensitivity of the modified Mallampati test (MMT) performed in the supine position is higher (69%) than for the MMT performed in sitting position (31%); whereas the specificity of the MMT in the supine and sitting positions is 61 and 84% respectively. Both tests are associated with comparable positive predictive values (23% for the sitting MMT and 21% for the supine MMT). The negative predictive value of the supine MMT is 93% compared 89% for the sitting MMT. The supine MMT is associated with high true positives (11 out of 123). The observation made by the authors is that the supine position is an equally good predictor of difficult intubation, because the positive predictive value of both positions is similar. The sitting MMT gives a more accurate negative predictive value. The data given in Table 1 stand the same and correctly predict the correlation between the two positions. We also confirm that the total number of patients is 123 and not 124. To conclude, the authors suggest that inability to perform the MMT in the sitting position should not raise concern because the test performed in the supine position gives comparable predictive results for airway assessment.

Background: A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that – at least in some cases – the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure. Results: Here we present a new procedure aimed at improving the sensitivity and/ or specificity of poorly-performing patterns. The procedure can be summarised as follows: 1. residues structurally conserved in different proteins, that are true positives for a pattern, are identified by means of a computational technique and by visual inspection. 2. the sequence positions of the structurally conserved residues falling outside the pattern are used to build extended sequence patterns. 3. the extended patterns are optimised on the SWISS-PROT database for their sensitivity and specificity. The method was applied to eight PROSITE patterns. Whenever structurally conserved residues are found in the surface region close to the pattern (seven out of eight cases), the addition of information inferred from structural analysis is shown to improve pattern selectivity and in some cases selectivity and sensitivity as well. In some of the cases considered the procedure allowed the identification of functionally interesting residues, whose biological role is also discussed. Conclusion: Our method can be applied to any type of functional motif or pattern (not only PROSITE ones) which is not able to select all and only the true positive hits and for which at least two true positive structures are available. The computational technique for the identification of structurally conserved residues is already available on request and will be soon accessible on our web server. The procedure is intended for the use of pattern database curators and of scientists interested in a specific protein family for which no specific or selective patterns are yet available.