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In this article we present a literature mining method RaJoLink that upgrades Swanson's ABC model approach to uncovering hidden relations from a set of articles in a given domain. When these relations are interesting from medical point of view and can be verified by medical experts, they represent new pieces of knowledge and can contribute to better understanding of diseases. In our study we analyzed biomedical literature about autism, which is a very complex and not yet sufficiently understood domain. On the basis of word frequency statistics several rare terms were identified with the aim of generating potentially new explanations for the impairments that are observed in the affected population. Calcineurin was discovered as a joint term in the intersection of their corresponding literature. Similarly, NF-kappaB was recognized as a joint term. Pairs of documents that point to potential relations between the identified joint terms and autism were also automatically detected. Expert evaluation confirmed the relevance of these relations. [ABSTRACT FROM AUTHOR]

This paper proposes a selection of knowledge technologies for health care planning and decision support in regional-level management of Slovenian public health care. Data mining and statistical techniques were used to analyze databases collected by a regional Public Heath Institute. Specifically, we addressed the problem of directing patients from primary health care centers to specialists. Decision support tools were used for resource modeling in terms of availability and accessibility of public health services for the population. Specifically, we analyzed organisational aspects of public health resources in one Sovenian region (Celje) with the goal to identify the areas that are atypical in terms of availability and accessibility of public health services. [ABSTRACT FROM AUTHOR]