Data structure-guided development of electrocardiographic signal characterization and classification

Conclusions: It was shown that granular representation of electrocardiographic signals is essential to data analysis and classification by providing a means to reveal and characterize the data structure and by providing prerequisites to construct pattern classifiers. The study also shows that fuzzy clusters deliver important structural information about the data that could be further quantified by looking into the content of clusters.
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Authors: Tags: Research Articles Source Type: research