Mining temporal patterns from health care data

Weiqiang Lin*, Mehmet A. Orgun, Graham J. Williams

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

9 Citations (Scopus)


This paper describes temporal data mining techniques for extracting information from temporal health records consisting of a time series of elderly diabetic patients' tests.We propose a data mining procedure to analyse these time sequences in three steps to identify patterns from any longitudinal data set. The first step is a structure-based search using wavelets to find pattern structures. The second step employs a value-based search over the discovered patterns using the statistical distribution of data values. The third step combines the results from the first two steps to form a hybrid model. The hybrid model has the expressive power of both wavelet analysis and the statistical distribution of the values. Global patterns are therefore identified.

Original languageEnglish
Title of host publicationData Warehousing and Knowledge Discovery - 4th International Conference, DaWaK 2002, Proceedings
EditorsY. Kambayashi, W. Winiwarter, M. Arikawa
Place of PublicationBerlin; Heidelberg
PublisherSpringer, Springer Nature
Number of pages10
Volume2454 LNCS
ISBN (Print)3540441239, 9783540441236
Publication statusPublished - 2002
Event4th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2002 - Aix-en-Provence, France
Duration: 4 Sept 20026 Sept 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2454 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349


Other4th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2002


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