Learn More
This paper gives a survey of contrast set mining (CSM), emerging pattern mining (EPM), and subgroup discovery (SD) in a unifying framework named supervised descriptive rule discovery. While all these research areas aim at discovering patterns in the form of rules induced from labeled data, they use different terminology and task definitions, claim to have(More)
The task addressed and the method proposed in this paper aim at improved understanding of differences between similar diseases. In particular we address the problem of distinguishing between thrombolic brain stroke and embolic brain stroke as an application of our approach of contrast set mining through subgroup discovery. We describe method-ological(More)
We analyzed fiber type composition of soleus and extensor digitorum longus (EDL) muscles of 3- to 19-month-old male and female inbred Lewis rats using histochemical demonstration of mATPase activity. The rats were divided into four groups of the mean age of 3, 6, 9 and 14 months. We found that the soleus muscle of 3-month-old rats contained significantly(More)
UNLABELLED The purpose of the study was to investigate the efficacy and safety of Cerebrolysin in patients with hemorrhagic stroke. The primary objective of this trial was to assess the clinical efficacy and safety of a 10-days course of therapy with a daily administration of Cerebrolysin (50 mL i.v. per day). The trial had to demonstrate that Cerebrolysin(More)
BACKGROUND In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance,(More)
According to the World Economic Forum, the diffusion of unsubstantiated rumors on online social media is one of the main threats for our society. The disintermediated paradigm of content production and consumption on online social media might foster the formation of homogeneous communities (echo-chambers) around specific worldviews. Such a scenario has been(More)
With the expanding of the Semantic Web and the availability of numerous ontologies which provide domain background knowledge and semantic descriptors to the data, the amount of semantic data is rapidly growing. The data mining community is faced with a paradigm shift: instead of mining the abundance of empirical data supported by the background knowledge,(More)
The paper presents an approach to computational knowledge discovery through the mechanism of bisociation. Bisociative reasoning is at the heart of creative, accidental discovery (e.g., serendipity), and is focused on finding unexpected links by crossing contexts. Contextu-alization and linking between highly diverse and distributed data and knowledge(More)