Analysis of time-series medical databases using multiscale structure matching and rough sets-based clustering technique

This paper presents a method for analyzing time-series laboratory examination databases. The key concept of this method is classification of temporal patterns using multiscale structure matching and a rough set-based clustering method. Multiscale matching enables us to capture similarity between two sequences of examinations from both short-term and long-term points of view. The rough-set based clustering technique is then applied to classify the sequences according to the relative similarity obtained through multiscale matching. In the experiments we show that this hybrid approach can be used to discover interesting temporal patterns hidden in the time-series databases