A Prediction Model to Diabetes using Artificial Metaplasticity

Marcano Cedeño, Alexis Enrique, Torres, Joaquin and Andina de la Fuente, Diego ORCID: https://orcid.org/0000-0001-7036-2646 (2011). A Prediction Model to Diabetes using Artificial Metaplasticity. En: "IWINAC'11 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications", 30/05/2011 - 03/06/2011, La Palma, Islas Canarias, España. ISBN 978-3-642-21325-0. pp. 418-425. https://doi.org/10.1007/978-3-642-21326-7_45.

Descripción

Título: A Prediction Model to Diabetes using Artificial Metaplasticity
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: IWINAC'11 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications
Fechas del Evento: 30/05/2011 - 03/06/2011
Lugar del Evento: La Palma, Islas Canarias, España
Título del Libro: IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications
Fecha: 2011
ISBN: 978-3-642-21325-0
Materias:
ODS:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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%

Más información

ID de Registro: 13269
Identificador DC: https://oa.upm.es/13269/
Identificador OAI: oai:oa.upm.es:13269
Identificador DOI: 10.1007/978-3-642-21326-7_45
Depositado por: Memoria Investigacion
Depositado el: 28 Nov 2012 10:33
Ultima Modificación: 21 Abr 2016 12:35