NDLI: Uncertainty rule generation on a home care database of heart failure patients

Content Provider	IEEE Xplore Digital Library
Author	Konias, S. Giaglis, G.D. Gogou, G. Bamidis, P.D. Maglaveras, N.
Copyright Year	2003
Description	Author affiliation: Lab. of Med. Informatics, Aristotelian Univ. of Thessaloniki, Greece (Konias, S.; Giaglis, G.D.; Gogou, G.; Bamidis, P.D.; Maglaveras, N.)
Abstract	In this paper we present the uncertainty rule generator tool and the algorithm used. This data-mining tool generates uncertainty rules as apart of the knowledge discovery in databases process and is tested upon a home-care database containing data from congestive heart failure patients over a period of approx. 10 months. This algorithm can handle dynamic data without the need of recovering the itemsets from the beginning. This is highly appropriate for a home-care monitoring system, where new records are constantly added. Moreover it can deal with missing values, since it uses flexible metrics, similar to those of other association rule algorithms. Finally this algorithm computes a certainty factor for each extracted rule, which is representative of its efficiency. In a future step, this extracted rule can be used on newly entered data, in order to predict the missing values, while its certainty factor will allow the exact estimation of error in this prediction.
Sponsorship	European Soc. of Cardiology Nat. Inst. of Health, USA
Starting Page	765
Ending Page	768
File Size	343814
Page Count	4
File Format	PDF
ISBN	078038170X
ISSN	02766547
DOI	10.1109/CIC.2003.1291269
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-09-21
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Databases Heart Data mining Testing Heuristic algorithms Itemsets Patient monitoring Condition monitoring Association rules
Content Type	Text
Resource Type	Article

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