Stochastic neural networks applied to dynamic glucose model for diabetic patients

Humberto M. Fonseca; Víctor H. Ortiz; Agustín I.cabrera

Stochastic neural networks applied to dynamic glucose model for diabetic patients

Humberto M. Fonseca, Víctor H. Ortiz, Agustín I.cabrera

Unidad Profesional Interdisciplinaria de Biotecnología (UPIBI)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

In this paper, we have described the use of stochastic neural networks in the Bergman's model of Insulin-glucose interaction, this model is observable in the sense of control theory, the variables in the model cannot be measured on-line but these were estimated by the neural network. The variables behavior are presented for a typical input like a food ingest in a period of time of 6 hours, the dynamic evolution of the insuline and glucose concentrations are showed for the perturbations and non perturbations model.

Idioma original	Inglés
Título de la publicación alojada	2004 1st International Conference on Electrical and Electronics Engineering, ICEEE
Páginas	522-525
Número de páginas	4
Estado	Publicada - 2004
Evento	2004 1st International Conference on Electrical and Electronics Engineering, ICEEE - Acapulco, México Duración: 8 sep. 2004 → 10 sep. 2004

Serie de la publicación

Nombre	2004 1st International Conference on Electrical and Electronics Engineering, ICEEE

Conferencia

Conferencia	2004 1st International Conference on Electrical and Electronics Engineering, ICEEE
País/Territorio	México
Ciudad	Acapulco
Período	8/09/04 → 10/09/04

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Otros archivos y enlaces

Enlace a la publicación en Scopus

Citar esto

@inproceedings{024eb72ec6544214b4ae7cf25311332b,

title = "Stochastic neural networks applied to dynamic glucose model for diabetic patients",

abstract = "In this paper, we have described the use of stochastic neural networks in the Bergman's model of Insulin-glucose interaction, this model is observable in the sense of control theory, the variables in the model cannot be measured on-line but these were estimated by the neural network. The variables behavior are presented for a typical input like a food ingest in a period of time of 6 hours, the dynamic evolution of the insuline and glucose concentrations are showed for the perturbations and non perturbations model.",

author = "Fonseca, {Humberto M.} and Ortiz, {V{\'i}ctor H.} and Agust{\'i}n I.cabrera",

year = "2004",

language = "Ingl{\'e}s",

isbn = "0780385314",

series = "2004 1st International Conference on Electrical and Electronics Engineering, ICEEE",

pages = "522--525",

booktitle = "2004 1st International Conference on Electrical and Electronics Engineering, ICEEE",

note = "2004 1st International Conference on Electrical and Electronics Engineering, ICEEE ; Conference date: 08-09-2004 Through 10-09-2004",

}

Fonseca, HM, Ortiz, VH & I.cabrera, A 2004, Stochastic neural networks applied to dynamic glucose model for diabetic patients. En 2004 1st International Conference on Electrical and Electronics Engineering, ICEEE. 2004 1st International Conference on Electrical and Electronics Engineering, ICEEE, pp. 522-525, 2004 1st International Conference on Electrical and Electronics Engineering, ICEEE, Acapulco, México, 8/09/04.

Stochastic neural networks applied to dynamic glucose model for diabetic patients. / Fonseca, Humberto M.; Ortiz, Víctor H.; I.cabrera, Agustín.
2004 1st International Conference on Electrical and Electronics Engineering, ICEEE. 2004. p. 522-525 (2004 1st International Conference on Electrical and Electronics Engineering, ICEEE).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Stochastic neural networks applied to dynamic glucose model for diabetic patients

AU - Fonseca, Humberto M.

AU - Ortiz, Víctor H.

AU - I.cabrera, Agustín

PY - 2004

Y1 - 2004

N2 - In this paper, we have described the use of stochastic neural networks in the Bergman's model of Insulin-glucose interaction, this model is observable in the sense of control theory, the variables in the model cannot be measured on-line but these were estimated by the neural network. The variables behavior are presented for a typical input like a food ingest in a period of time of 6 hours, the dynamic evolution of the insuline and glucose concentrations are showed for the perturbations and non perturbations model.

AB - In this paper, we have described the use of stochastic neural networks in the Bergman's model of Insulin-glucose interaction, this model is observable in the sense of control theory, the variables in the model cannot be measured on-line but these were estimated by the neural network. The variables behavior are presented for a typical input like a food ingest in a period of time of 6 hours, the dynamic evolution of the insuline and glucose concentrations are showed for the perturbations and non perturbations model.

UR - http://www.scopus.com/inward/record.url?scp=24644447704&partnerID=8YFLogxK

M3 - Contribución a la conferencia

AN - SCOPUS:24644447704

SN - 0780385314

SN - 9780780385313

T3 - 2004 1st International Conference on Electrical and Electronics Engineering, ICEEE

SP - 522

EP - 525

BT - 2004 1st International Conference on Electrical and Electronics Engineering, ICEEE

T2 - 2004 1st International Conference on Electrical and Electronics Engineering, ICEEE

Y2 - 8 September 2004 through 10 September 2004

ER -

Stochastic neural networks applied to dynamic glucose model for diabetic patients

Resumen

Serie de la publicación

Conferencia

ODS de las Naciones Unidas

Otros archivos y enlaces

Huella

Citar esto