Abstract
Physicians are required to interpret, abstract and present in free-text large amounts of clinical data in their daily tasks. This is especially true for chronic-disease domains, but also in other clinical domains. In our previous work, we have suggested a general framework for performing this task, given a time-oriented clinical database, and appropriate formal abstraction and summarization knowledge. We have recently developed a prototype system, CliniText, which demonstrates our ideas. Our prototype combines knowledge-based temporal data abstraction, textual summarization, abduction, and natural-language generation techniques, to generate an intelligent textual summary of longitudinal clinical data. We demonstrate both our methodology, and the feasibility of providing a free-text summary of longitudinal electronic patient records, by generating a discharge summary of a patient from the MIMIC database, who had undergone a Coronary Artery Bypass Graft operation.
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Goldstein, A., Shahar, Y. (2013). Implementation of a System for Intelligent Summarization of Longitudinal Clinical Records. In: Riaño, D., Lenz, R., Miksch, S., Peleg, M., Reichert, M., ten Teije, A. (eds) Process Support and Knowledge Representation in Health Care. ProHealth KR4HC 2013 2013. Lecture Notes in Computer Science(), vol 8268. Springer, Cham. https://doi.org/10.1007/978-3-319-03916-9_6
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DOI: https://doi.org/10.1007/978-3-319-03916-9_6
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