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A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN

Diabetes is difficult to control and it is important to manage the diabetic’s blood sugar level and prevent the associated complications by appropriate diabetic treatment. This paper proposes a system that can provide appropriate management for diabetes patients, according to their blood sugar level...

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Detalles Bibliográficos
Autores principales: Lee, Malrey, Gatton, Thomas M., Lee, Keun-Kwang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3274186/
https://www.ncbi.nlm.nih.gov/pubmed/22319334
http://dx.doi.org/10.3390/s100403934
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author Lee, Malrey
Gatton, Thomas M.
Lee, Keun-Kwang
author_facet Lee, Malrey
Gatton, Thomas M.
Lee, Keun-Kwang
author_sort Lee, Malrey
collection PubMed
description Diabetes is difficult to control and it is important to manage the diabetic’s blood sugar level and prevent the associated complications by appropriate diabetic treatment. This paper proposes a system that can provide appropriate management for diabetes patients, according to their blood sugar level. The system is designed to send the information about the blood sugar levels, blood pressure, food consumption, exercise, etc., of diabetes patients, and manage the treatment by recommending and monitoring food consumption, physical activity, insulin dosage, etc., so that the patient can better manage their condition. The system is based on rules and the K Nearest Neighbor (KNN) classifier algorithm, to obtain the optimum treatment recommendation. Also, a monitoring system for diabetes patients is implemented using Web Services and Personal Digital Assistant (PDA) programming.
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spelling pubmed-32741862012-02-08 A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN Lee, Malrey Gatton, Thomas M. Lee, Keun-Kwang Sensors (Basel) Article Diabetes is difficult to control and it is important to manage the diabetic’s blood sugar level and prevent the associated complications by appropriate diabetic treatment. This paper proposes a system that can provide appropriate management for diabetes patients, according to their blood sugar level. The system is designed to send the information about the blood sugar levels, blood pressure, food consumption, exercise, etc., of diabetes patients, and manage the treatment by recommending and monitoring food consumption, physical activity, insulin dosage, etc., so that the patient can better manage their condition. The system is based on rules and the K Nearest Neighbor (KNN) classifier algorithm, to obtain the optimum treatment recommendation. Also, a monitoring system for diabetes patients is implemented using Web Services and Personal Digital Assistant (PDA) programming. Molecular Diversity Preservation International (MDPI) 2010-04-19 /pmc/articles/PMC3274186/ /pubmed/22319334 http://dx.doi.org/10.3390/s100403934 Text en © 2010 by the authors; licensee MDPI, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Lee, Malrey
Gatton, Thomas M.
Lee, Keun-Kwang
A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN
title A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN
title_full A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN
title_fullStr A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN
title_full_unstemmed A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN
title_short A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN
title_sort monitoring and advisory system for diabetes patient management using a rule-based method and knn
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3274186/
https://www.ncbi.nlm.nih.gov/pubmed/22319334
http://dx.doi.org/10.3390/s100403934
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