Breast cancer classification applying artificial metaplasticity algorithm

On the Biological Plausibility of Artificial Metaplasticity

“…According to Mockett and colleagues [27] metaplasticity is inherently a homosynaptic phenomenon in contrast to the heterosynaptic nature of the BCM rule. Finally, Artola, Brocher and Singer's [28]) extended model (ABS model) is not analytical, as those just discussed, but is based on empirical experimental data. In the ABS model, LTP and LTD thresholds shift to lower values for higher levels of the activation of neighbouring synapses.…”

“…In its implementation characteristics, the proposed AMP model follows closer to the BCM model. We do not pretend to determine its superiority, but neurobiology inspires computer science and vice versa, and we report that the empirical results of AMP show a great potential, in terms of improving learning and therefore performance in most cases, no matter in what multidisciplinary application is applied [1,17,18,28].…”

A Prediction Model to Diabetes Using Artificial Metaplasticity

“…Recently, Ropero-Peláez [10], Andina [11] and Marcano-Cedeño [12] have introduced and modeled the biological property metaplasticity in the field of artificial neural networks (ANN), obtaining excellent results.…”

“…There are different artificial metaplasticity (AMP) models [12]. However, of all AMP models tested by the authors, the most efficient model (as a function of learning time and performance) is the approach that connects metaplasticity and Shannon's information theory, which establishes that less frequent patterns carry more information than frequent patterns [13].…”

“…Biological metaplasticity favors synaptic strengthening for low-level synaptic activity, while the opposite occurs for high level activity. The model is applicable to general ANNs [11,12], although in this paper it has been implemented for a multilayer perceptron (MLP).…”