Abstract
The analysis of customized decisions during hypertension management in a specialized unit requires a detailed representation of clinical cases. We are building a specific ontology to code medical records and process them with computerized tools. Relevant concepts to describe and justify medical decisions are extracted from three sources: (i) Clinical guidelines; (ii) Items of the semi-structured medical record form used in the clinical unit; (iii) Free-text answers from 5,000 completed record forms. Combining terminological sources is mandatory to cover the whole spectrum of possible justifications for clinical decisions, including contextual specificities and patients’ particulars.
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Steichen, O., Daniel-Le Bozec, C., Jaulent, MC., Charlet, J. (2007). Building an Ontology of Hypertension Management. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science(), vol 4594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73599-1_39
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DOI: https://doi.org/10.1007/978-3-540-73599-1_39
Publisher Name: Springer, Berlin, Heidelberg
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