Abstract
This paper describes the highly scalable open source framework DrugFusion developed within the European Union(EU) project TIMBUS. It was designed by using Case-Based Reasoning(CBR) methodology to provide intelligent assistance for doctors and pharmacists in drug prescription process. DrugFusion analyses adverse event reports (AER)s published by United States Food and Drug Administration (FDA) and generates knowledge containers, which are used for efficient and accurate retrieval of similar treatment cases curried out in the past. DrugFusion uses the adaptation knowledge to produce a set of recommendations for medical practitioners, which allows them to make the most competent decision in planning a patient treatment. These recommendations include the most appropriate set of treatment drugs and warnings for the most likely adverse events. Considering the high complexity of the developed architecture, the main focus of this paper is on covering the similarity and indexing knowledge, used by the DrugFusion retrieval process.
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Galushka, M., Gilani, W. (2014). DrugFusion - Retrieval Knowledge Management for Prediction of Adverse Drug Events. In: Abramowicz, W., Kokkinaki, A. (eds) Business Information Systems. BIS 2014. Lecture Notes in Business Information Processing, vol 176. Springer, Cham. https://doi.org/10.1007/978-3-319-06695-0_2
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DOI: https://doi.org/10.1007/978-3-319-06695-0_2
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