Abstract
Therapy management needs sophisticated patient monitoring and therapy planning, especially in high-frequency domains, like Neonatal Intensive Care Units (NICUs), where complex data sets are collected every second. An elegant method to tackle this problem is the use of time-oriented, skeletal plans. Asgaard is a framework for the representation, visualization, and execution of such plans. These plans work on qualitative abstracted time-oriented data which closely resemble the concepts used by experienced clinicians.
This papers presents the data abstraction unit of the Asgaard system. It provides a range of connectable data abstraction methods bridging the gap between the raw data collected by monitoring devices and the abstract concepts used in therapeutic plans. The usability of this data abstraction unit is demonstrated by the implementation of a controller for the automated optimization of the fraction of inspired oxygen (FiO2). The use of the time-oriented data abstraction methods results in safe and smooth adjustment actions of our controller in a neonatal care setting.
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Seyfang, A., Miksch, S., Horn, W., Urschitz, M.S., Popow, C., Poets, C.F. (2001). Using time-oriented data abstraction methods to optimize oxygen supply for neonates. In: Quaglini, S., Barahona, P., Andreassen, S. (eds) Artificial Intelligence in Medicine. AIME 2001. Lecture Notes in Computer Science(), vol 2101. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48229-6_31
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DOI: https://doi.org/10.1007/3-540-48229-6_31
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