Pozyskiwanie wiedzy probabilistycznej dla modelu zakażeń szpitalnych - Valenta, Marek A.; Zygmunt, Anna (Probabilistic knowledge acquisition for the nosocomial infections model, 2005)
Experts and their experience are of great importance for building the probabilistic models of domain knowledge, on condition that these experts are able to convert their experience into the knowledge base components. However, in many cases one can find that the domain databases could be very useful. On the basis of that database one can create knowledge model. Such model, as a rule, shouldn’t require considerable amount of work for their verification, because it should be automatically conect image of the described reality. Making such assumption, we will present the process of knowledge acquisition for the nosocomial infections model, where data about the nosocomial infections will be the source of that knowledge. These data were acquired on Polish Society of Hospital Infection initiative from above 100 hospitals in Poland. Within research, in Department of Computer Science AGH the central database, acquiring data from distributed hospital databases, was created. Nosocomial infection database (storing data from 1999-2000) was used to make research about automatic knowledge acquisition methods for building the probabilistic models based on bayes net. Presented research show the usability of such process on the basis of BN Power Software. Analysis of the following phase of the process show its complexity and conditions having the significant impact on that process success. In the article the exemplary results will be presented. Conclusions indicate the immense impact input data on the created model quality. Theses conclusions also concern the recommendations about the content and structure of the future systems acquiring nosocomial infection data, so one could automatically use them to the probabilistic knowledge model building.
Prace Naukowe Akademii Ekonomicznej we Wrocławiu; 2005; nr 1064, s. 290-301