A unifying approach to temporal constraint reasoning
Artificial Intelligence
Pruning and summarizing the discovered associations
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Maintaining knowledge about temporal intervals
Communications of the ACM
Temporal representation and reasoning in artificial intelligence: Issues and approaches
Annals of Mathematics and Artificial Intelligence
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Mining Similar Temporal Patterns in Long Time-Series Data and Its Application to Medicine
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Mining hepatitis data with temporal abstraction
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Intelligent analysis of clinical time series: an application in the diabetes mellitus domain
Artificial Intelligence in Medicine
Review: Knowledge discovery in medicine: Current issue and future trend
Expert Systems with Applications: An International Journal
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Various data mining methods have been developed last few years for hepatitis study using a large temporal and relational database given to the research community. In this work we introduce a novel temporal abstraction method to this study by detecting and exploiting temporal patterns and relations between events in viral hepatitis such as "event A slightly happened before event B and B simultaneously ended with event C". We developed algorithms to first detect significant temporal patterns in temporal sequences and then to identify temporal relations between these temporal patterns. Many findings by data mining methods applied to transactions/graphs of temporal relations shown to be significant by physician evaluation and matching with published in Medline.