Mining Statistically Significant Associations for Exploratory Analysis of Human Sleep Data.

Mining Statistically Significant Associations for Exploratory Analysis of Human Sleep Data.

We introduce a specialized association rule mining technique that can extract patterns from complex sleep data comprising polysomnographic recordings, clinical summaries, and sleep questionnaire responses. The rules mined can describe associations among temporally annotated events and questionnaire...

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Detalles Bibliográficos
Publicado en:IEEE Transactions on information technology in biomedicine 10, 3 (2006).
Autor principal: Laxminarayan, P.
Formato: Artículo
Lenguaje:English
Materias:
Clinical summary information.
Data mining.
Human sleep data.
Logistic regression.
Medical diagnosis.
Moderate caffeine intake.
Polysonmographic time-series data.
Rapid eye movement sleep stage.
Rule mining technique.
Sleep questionnaire response.
Statistical analysis.