The standard method for immunoscreening of a cDNA expression library is time-consuming becauseof the production of a large proportion of false positives during the first and second round of screening.This problem is more important when a sensitive chemiluminescence detection system is used. Due tothe high sensitivity of the detection system, there is a need to avoid false posi...

Standard classification allocates all processed elements to given classes. Such type of classification assumes that there are only native and no foreign elements, i.e. all processed elements are included in given classes. The quality of standard classification can be measured by two factors: numbers of correctly and incorrectly classified elements, called True Positives and False Positives. Adm...

BACKGROUND Urine-bilirubin measurement is common in urinalysis dipsticks, which are known to yield a high rate of false positive results. We evaluated the usefulness of this test after multiple physicians in our system reported that they do not act on positive dipstick urine bilirubin findings. METHODS We queried past records to determine how many samples with positive urine bilirubin results...

Red cells coated with lipopolysaccharides from three different strains of Neisseria gonorhoeae have been used as antigens in a haemagglutination test for gonococcal antibodies. For each strain the geometric mean titre in sera from 50 male and 25 female patients was significantly higher than that in 50 normal controls. The most useful smooth strain, G1, picked out 84% of females and 46% of males...

In certain applications there may only be positive samples available to to learn concepts of a class of interest, and this has to be done properly, i. e. the hypothesis space has to coincide with the concept class, and without false positives, i. e. the hypothesis always has be a subset of the real concept (one-sided error). For the well studied class of k-term DNF formulas it has been known th...

The accurate identification of promoter regions and transcription start sites is a challenge to the construction of human transcription regulation networks. Thus, an efficient prediction method based on theoretical formulation is necessary for this purpose. We used the method of increment diversity with quadratic discriminant analysis (IDQD) to predict transcription start sites (TSS). The metho...

Most supervised machine learning research assumes the training set is a random sample from the target population, thus the class distribution is invariant. In real world situations, however, the class distribution changes, and is known to erode the effectiveness of classifiers and calibrated probability estimators. This paper focuses on the problem of accurately estimating the number of positiv...

Protein-protein interaction data obtained from high-throughput experiments is thought to have a large number of false positives i.e. interactions that are spurious and do not occur in the cell. This fraction is estimated to be as high as 50% in yeast [3]. Hence it is important to quantitate the reliability of these interactions and identify those that are true positives i.e. those that actually...