University of Antwerp

About: University of Antwerp is a education organization based out in Antwerp, Belgium. It is known for research contribution in the topics: Population & Context (language use). The organization has 16682 authors who have published 48837 publications receiving 1689748 citations. The organization is also known as: Universiteit Antwerpen & UAntwerp.

Consensus for tinnitus patient assessment and treatment outcome measurement: Tinnitus Research Initiative meeting, Regensburg, July 2006.

Abstract: There is widespread recognition that consistency between research centres in the ways that patients with tinnitus are assessed and outcomes following interventions are measured would facilitate more effective co-operation and more meaningful evaluations and comparisons of outcomes. At the first Tinnitus Research Initiative meeting held in Regensburg in July 2006 an attempt was made through workshops to gain a consensus both for patient assessments and for outcome measurements. It is hoped that this will contribute towards better cooperation between research centres in finding and evaluating treatments for tinnitus by allowing better comparability between studies.

Mining All Non-derivable Frequent Itemsets

Abstract: Recent studies on frequent itemset mining algorithms resulted in significant performance improvements. However, if the minimal support threshold is set too low, or the data is highly correlated, the number of frequent itemsets itself can be prohibitively large. To overcome this problem, recently several proposals have been made to construct a concise representation of the frequent itemsets, instead of mining all frequent itemsets. The main goal of this paper is to identify redundancies in the set of all frequent itemsets and to exploit these redundancies in order to reduce the result of a mining operation. We present deduction rules to derive tight bounds on the support of candidate itemsets. We show how the deduction rules allow for constructing a minimal representation for all frequent itemsets. We also present connections between our proposal and recent proposals for concise representations and we give the results of experiments on real-life datasets that show the effectiveness of the deduction rules. In fact, the experiments even show that in many cases, first mining the concise representation, and then creating the frequent itemsets from this representation outperforms existing frequent set mining algorithms.

Congenital hearing loss.

Abstract: Congenital hearing loss (hearing loss that is present at birth) is one of the most prevalent chronic conditions in children. In the majority of developed countries, neonatal hearing screening programmes enable early detection; early intervention will prevent delays in speech and language development and has long-lasting beneficial effects on social and emotional development and quality of life. A diagnosis of hearing loss is usually followed by a search for an underlying aetiology. Congenital hearing loss might be attributed to environmental and prenatal factors, which prevail in low-income settings; congenital infections, particularly cytomegalovirus infection, are also a common risk factor for hearing loss. Genetic causes probably account for the majority of cases in developed countries; mutations can affect any component of the hearing pathway, in particular, inner ear homeostasis (endolymph production and maintenance) and mechano-electrical transduction (the conversion of a mechanical stimulus into electrochemical activity). Once the underlying cause of hearing loss is established, it might direct therapeutic decision making and guide prevention and (genetic) counselling. Management options include specific antimicrobial therapies, surgical treatment of craniofacial abnormalities and implantable or non-implantable hearing devices. An improved understanding of the pathophysiology and molecular mechanisms that underlie hearing loss and increased awareness of recent advances in genetic testing will promote the development of new treatment and screening strategies.