The amount of data produced within Health Informatics has grown to be quite vast, and
analysis of this Big Data grants potentially limitless possibilities for knowledge to be gained …

The modern modeling of flotation processes has been burdened for years with limitations of
classical mathematics and modeling. The emergence of soft computing methods has also …

BACKGROUND: The multiplicity of information sources for data acquisition in modern
intensive care units (ICUs) makes the resulting databases particularly susceptible to missing …

When individual classifiers are combined appropriately, a statistically significant increase in
classification accuracy is usually obtained. Multiple classifier systems are the result of …

Feature selection (FS) is an important task which can significantly affect the performance of
image classification and recognition. In this paper, we present a feature selection algorithm …

This paper addresses the classification problem with imperfect data. More precisely, it
extends standard decision trees to handle uncertainty in both building and classification …

Patient readmissions to intensive care units (ICUs) are associated with increased mortality,
morbidity and costs. Current models for predicting ICU readmissions have moderate …

OBJECTIVES: To reduce unnecessary lab testing by predicting when a proposed future lab
test is likely to contribute information gain and thereby influence clinical management in …

Abstract Machine learning models for exploring structure-property relation for hydroxyapatite
nanoparticles (HANPs) are still lacking. A multiscale multisource dataset is presented …

The available set of potential features in real-world databases is sometimes very large, and
it can be necessary to find a small subset for classification purposes. One of the most …