_{[News Viscovery]}

Horn (NL) / Vienna (AT), 12 September 2018 Together with Ingrid Augustin and her colleagues from our long term customer CIRO+, we published the article The respiratory physiome: clustering based on a comprehensive lung function assessment in patients with COPD in PLOS ONE.

The aim of this paper is to provide a comprehensive description of lung function for patients with chronic obstructive pulmonary disease (COPD) and study its connection to functional performance and health status. The Viscovery SOMine cluster model shows that lung-function impairment is a multidimensional problem, which cannot be characterized by a single measurement. In addition, it is shown that the lung-function profile alone is a poor predictor for functional performance, highlighting the necessity of additional performance tests and questionnaires to provide optimal treatment for patients.

Find the full open access article at journals.plos.org

_{[News Viscovery]}

Vienna / Austria, 29 June 2018 Viscovery has launched version 7.2 of its Viscovery® SOMine® visual data mining suite. The new version offers a set of features for improved performance in Big Data preprocessing, as well as for advanced annotation and interpretation of explorative models on multiple semantic levels.

Viscovery® SOMine® v7.2 comes with considerable performance improvements for preprocessing of Big Data. By using single-instance caching in data and model processing, the runtime for applying bulky definitions of nominal variables has been significantly reduced.

Annotation of the map with textual labels has been extended to allow thumbnails. For example, an associated image document, such as a photo, can be displayed at the location in the Viscovery map to which a patient has been classified. Another new feature allows users to manage labels, group them hierarchically, and hide or show these groupings. This helps users annotate and interpret the Viscovery map on different semantic levels.

The complete list of innovations is available at viscovery.net/data-sheets.

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_{[News Viscovery]}

Marburg (DE) / Trondheim (NO) / Maastricht (NL) / Horn (NL) / Vienna (AT), 1 July 2018 Viscovery and our transnational group of scientific and clinical collaborators just started the interdisciplinary project ERACo SysMed-COPD.

The main aim of this project is to develop a clinical decision support system for chronic obstructive pulmonary disease (COPD), which will help doctors and medical staff to find the best therapeutic option for the individual patient. Data about several thousand patients from different patient cohorts at different clinics will be used to build a model for identifying possible risk factors and expectable outcomes to respiratory therapy.

The project is part of the EU framework ERACoSysMed for Systems Medicine to address clinical needs and is co-funded by the national funding institutions

• Bundesministerium für Bildung und Forschung (BMBF), Germany,
• The Austrian Science Fund (FWF), Austria,
• The Research Council of Norway (RCN), Norway,
• Zorgonderzoek Nederland (ZON), Netherlands.

Read more about the project at www.uni-marburg.de.

_{[News Viscovery]}

Vienna / Austria, 31 May 2017 Data mining and data visualization specialist Viscovery Software GmbH has released version 7.1 of its visual data-mining suite Viscovery® SOMine. It comes with a unique innovation that empowers exploration of Big Data faster than ever.

Besides numerous usability improvements, the new SOMine version provides various additional functionality: visual exploration of multivariate Big Data, analysis of multiple attribute correlations, determination of score groups with maximal response, and the option to display thumbnail images associated to the ordered data records in the Viscovery model map. The complete list of innovations is available at viscovery.net/data-sheets.

Interactive exploration of Big Data has been made possible by allowing arbitrary numbers of records to be represented in Viscovery maps. The innovation is based on Viscovery maps as representations for large data distributions which, although created from samples of the data, are nevertheless applicable to the entirety of the data. The map visualization provides instantaneous descriptive statistics as well as real-time access to original data records. Clusters and statistical profiles can be created, modified and determined in fractions of a second, even for very large datasets. This opens the world of interactive data exploration to Big Data.

Visit the Viscovery website to learn from an example how data scientists used the power of the Viscovery Big Data feature to rapidly visualize and explore tens of millions of US mortality records – with surprising results.

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