Neural and traditional techniques in diagnostic ECG classification.

Neural and traditional techniques have been compared for the particular task of automatic ECG analysis. A large validated ECG database has been used. Statistical methods, neural architectures with supervised and unsupervised learning, and a neuro-fuzzy architecture have been considered. The results from the connectionist approach are always at least comparable with those coming from more traditional classification methods. But the best performances have been obtained by the combination of the connectionist with the fuzzy approach.