A prediction model to diabetes using artificial metaplasticity

Authors:
Alexis Marcano-Cedeño;Joaquín Torres;Diego Andina
Affiliations:
Group for Automation in Signals and Communications, Technical University of Madrid;Group for Automation in Signals and Communications, Technical University of Madrid;Group for Automation in Signals and Communications, Technical University of Madrid
Venue:
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
Year:
2011

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Abstract

Diabetes is the most common disease nowadays in all populations and in all age groups. Different techniques of artificial intelligence has been applied to diabetes problem. This research proposed the artificial metaplasticity on multilayer perceptron (AMMLP) as prediction model for prediction of diabetes. The Pima Indians diabetes was used to test the proposed model AMMLP. The results obtained by AMMLP were compared with other algorithms, recently proposed by other researchers, that were applied to the same database. The best result obtained so far with the AMMLP algorithm is 89.93%.