Abstract
In this paper, we describe an approach to utilize Case-Based Reasoning (CBR) methods for trend prognoses for medical problems. Since using conventional methods for reasoning over time does not fit for course predictions without medical knowledge of typical course pattern, we have developed abstraction methods suitable for integration into our Case-Based Reasoning system ICONS. These methods combine medical experience with prognoses of multiparametric courses. We apply them to the monitoring of the kidney function in an Intensive Care Unit (ICU) setting. We generate course-characteristic trend descriptions of the renal function over the course of time. Using Case-Based Reasoning retrieval methods, we search in the case base for courses similar to the, current trend descriptions. We present a current course together with similar courses as comparisons and as possible prognoses to the user.
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Schmidt, R., Gierl, L. (2000). Prognoses for Multiparametric Time Courses. In: Brause, R.W., Hanisch, E. (eds) Medical Data Analysis. ISMDA 2000. Lecture Notes in Computer Science, vol 1933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39949-6_5
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DOI: https://doi.org/10.1007/3-540-39949-6_5
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