Abstract
By exploiting advances in natural language processing, we believe that information contained in unstructured texts can be leveraged to facilitate risk modeling and decision support in healthcare. In this paper, we present our initial investigations into dependence relation extraction and aggregation into a Bayesian Belief Network structure. Our results are based on a corpus composed of MEDLINE® abstracts dealing with breast cancer risk factors.
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Deleris, L., Deparis, S., Sacaleanu, B., Tounsi, L. (2013). Risk Information Extraction and Aggregation. In: Perny, P., Pirlot, M., Tsoukiàs, A. (eds) Algorithmic Decision Theory. ADT 2013. Lecture Notes in Computer Science(), vol 8176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41575-3_12
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DOI: https://doi.org/10.1007/978-3-642-41575-3_12
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