Abstract
The Intensive Care Unit (ICU) domain generates large volumes of patient data which can be used in medical research. However, inaccuracies often exist in this data and due to the data's size and domain complexity, automated approaches are required to associate a level of quality and trust with the data. We describe a computational framework to perform such assessments based on semantic web technologies. Linked data enables integration with other datasets, which can be used along with details of the data's provenance and medical domain knowledge from appropriate ontologies. We have successfully applied the framework to two types of ICUs: general medical and traumatic brain injury. © 2013 Springer-Verlag.
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CITATION STYLE
Moss, L., Corsar, D., Piper, I., & Kinsella, J. (2013). Trusting Intensive Care Unit (ICU) medical data: A semantic web approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7885 LNAI, pp. 68–72). Springer Verlag. https://doi.org/10.1007/978-3-642-38326-7_10
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