Sökning: L773:2168 2194 OR L773:2168 2208 >
Data-driven rule mi...
Data-driven rule mining and representation of temporal patterns in physiological sensor data
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- Banaee, Hadi, 1986- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,AASS
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- Loutfi, Amy, 1978- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,AASS
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(creator_code:org_t)
- 2015
- 2015
- Engelska.
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Ingår i: IEEE journal of biomedical and health informatics. - 2168-2194 .- 2168-2208. ; 19:5, s. 1557-1566
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Mining and representation of qualitative patterns is a growing field in sensor data analytics. This paper leverages from rule mining techniques to extract and represent temporal relation of prototypical patterns in clinical data streams. The approach is fully data-driven, where the temporal rules are mined from physiological time series such as heart rate, respiration rate, and blood pressure. To validate the rules, a novel similarity method is introduced, that compares the similarity between rule sets. An additional aspect of the proposed approach has been to utilize natural language generation techniques to represent the temporal relations between patterns. In this study, the sensor data in the MIMIC online database was used for evaluation, in which the mined temporal rules as they relate to various clinical conditions (respiratory failure, angina, sepsis, ...) were made explicit as a textual representation. Furthermore, it was shown that the extracted rule set for any particular clinical condition was distinct from other clinical conditions.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Data-driven modeling
- health informatics
- linguistic representation
- pattern abstraction
- physiological sensor data
- sensor data analysis
- temporal rule mining
- Datavetenskap
- Computer Science
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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