PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Temporal Data Mining Using Multilevel-Local Polynominal Models
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
Temporal Data Mining Using Hidden Markov-Local Polynomial Models
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
Pattern Discovery on Australian Medical Claims Data-A Systematic Approach
IEEE Transactions on Knowledge and Data Engineering
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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.