Abstract
In this paper we present a new approach for the intelligent analysis of longitudinal data coming from diabetic patients home monitoring. This approach consists in exploiting temporal abstractions to pre-process the raw data and to obtain a new time series of abstract episodes, whose features are then interpreted through statistical and probabilistic techniques. We finally show the application of this methodology on the data of two diabetic patients monitored for six months.
Keywords
- Time Slice
- Temporal Abstraction
- Intelligent Data Analysis
- Abstract State
- Blood Glucose Level Measurement
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 1997 Springer-Verlag
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Bellazzi, R., Larizza, C., Riva, A. (1997). Interpreting longitudinal data through temporal abstractions: An application to diabetic patients monitoring. In: Liu, X., Cohen, P., Berthold, M. (eds) Advances in Intelligent Data Analysis Reasoning about Data. IDA 1997. Lecture Notes in Computer Science, vol 1280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052848
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DOI: https://doi.org/10.1007/BFb0052848
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