Presently most adolescent anxiety disorder screening instruments make their determination of running a high risk for an anxiety disorder on the basis of a cut-off score measured by a single screening which can lead to false positives. Therefore, the goal of this study is to examine whether a repeated administration of the SCARED screening instrument for DSM-5 anxiety disorder symptoms could hel...

Many of today's Intrusion Detection Systems (IDSs) suffer from high rates of false positives [1]. False positives are a severe problem because investigating them takes time and energy. Even worse, if the load of false positives is too high, security personnel might become negligent and start to ignore alarms. Improving this situation is difficult [1, 2]. One possible solution is to use highly s...

Functional cranial near-infrared spectroscopy (NIRS) has been widely used to investigate the haemodynamic changes which occur in response to functional activation. The technique exploits the different absorption spectra of oxy- and deoxy-haemoglobin ([HbO2] [HHb]) in the near-infrared region to measure the changes in oxygenation and haemodynamics in the cortical tissue. The aim of this study wa...

Association rule mining is an important problem in the data mining area. It enumerates and tests a large number of rules on a dataset and outputs rules that satisfy user-specified constraints. Due to the large number of rules being tested, rules that do not represent real systematic effect in the data can satisfy the given constraints purely by random chance. Hence association rule mining often...

Group testing is a frequently used tool to identify an unknown set of defective (positive) elements out of a large collection of elements by testing subsets (pools) for the presence of defectives. Various models have been studied in the literature. The most studied case concerns only two types (defective and non-defective) of elements in the given collection. This paper studies a novel and natu...

In the search for new cancer subtypes by gene expression profiling, it is essential to avoid misclassifying samples of unknown subtypes as known ones. In this paper, we evaluated the false positive error rates of several classification algorithms through a 'null test' by presenting classifiers a large collection of independent samples that do not belong to any of the tumor types in the training...

Background The contrasting groups' standard setting method is commonly used for consequences analysis in validity studies for performance in medicine and surgery. The method identifies a pass/fail cut-off score, from which it is possible to determine false positives and false negatives based on observed numbers in each group. Since groups in validity studies are often small, e.g., due to a limi...

The presence of microaneurysms in the eye is one of the early signs of diabetic retinopathy, which is one of the leading causes of vision loss. We have been investigating a computerized method for the detection of microaneurysms on retinal fundus images, which were obtained from the Retinopathy Online Challenge (ROC) database. The ROC provides 50 training cases, in which “gold standard” locatio...

Large-scale presence-absence monitoring programs have great promise for many conservation applications. Their value can be limited by potential incorrect inferences owing to observational errors, especially when data are collected by the public. To combat this, previous analytical methods have focused on addressing non-detection from public survey data. Misclassification errors have received le...

This paper presents a new method of measuring performance when positives are rare and investigates whether Chomskylike grammar representations are useful for learning accurate comprehensible predictors of members of biological sequence families. The positive-only learning framework of the Inductive Logic Programming (ILP) system CProgol is used to generate a grammar for recognising a class of p...