Key result
Automatic heartbeat classification methods achieved high accuracies using local learning sets, whereas the global learning set yielded the worst results.
Local learning sets provide higher accuracy for automatic heartbeat classification compared to global learning sets across multiple machine learning methods.
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Local learning sets may boost automated ECG classification accuracy; leaves open whether global models can be refined for clinical use.
Jekova et al. (2007) studied Cardiac dysfunctions. Automatic heartbeat classification methods (Kth nearest neighbour, neural networks, discriminant analysis, fuzzy logic) vs. Different learning sets (global, basic, local) was evaluated on Classification accuracy. Automatic heartbeat classification methods achieved high accuracies using local learning sets, whereas the global learning set yielded the worst results.
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