Dosage planning for diabetes patients using data mining methods

Emirhan Gülçin Yildirim; Adem Karahoca; Tamer Uçar

doi:10.1016/j.procs.2011.01.018

Dosage planning for diabetes patients using data mining methods

Emirhan Gülçin Yildirim, Adem Karahoca, Tamer Uçar

AI Engineering

Research output: Contribution to journal › Conference article › peer-review

24 Citations (Scopus)

Abstract

The condition of high blood sugar (glucose) level is called as diabetes mellitus. Cause of this disease can be either insufficient insulin production or improper response of body cell to insulin. Diabetes patients should use different drugs in order to keep their blood sugar level within normal range values. The purpose of this study is to develop a data mining model for which will predict a suitable dosage planning for diabetes patients. Medical records of 89 different patient records were used in this study. 318 diabetes assays were extracted using these patient records. ANFIS and Rough Set methods were used for dosage planning objective. According to the results of ANFIS and Rough Set methods, ANFIS is a more successful and reliable method for diabetes drug planning objective when compared to Rough Set method.

Original language	English
Pages (from-to)	1374-1380
Number of pages	7
Journal	Procedia Computer Science
Volume	3
DOIs	https://doi.org/10.1016/j.procs.2011.01.018
Publication status	Published - 2011
Event	1st World Conference on Information Technology, WCIT-2010 - Istanbul, Turkey Duration: 6 Oct 2010 → 10 Oct 2010

Keywords

ANFIS
Diabetes
Dosage planning
Rough set theory

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.procs.2011.01.018

Cite this

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title = "Dosage planning for diabetes patients using data mining methods",

abstract = "The condition of high blood sugar (glucose) level is called as diabetes mellitus. Cause of this disease can be either insufficient insulin production or improper response of body cell to insulin. Diabetes patients should use different drugs in order to keep their blood sugar level within normal range values. The purpose of this study is to develop a data mining model for which will predict a suitable dosage planning for diabetes patients. Medical records of 89 different patient records were used in this study. 318 diabetes assays were extracted using these patient records. ANFIS and Rough Set methods were used for dosage planning objective. According to the results of ANFIS and Rough Set methods, ANFIS is a more successful and reliable method for diabetes drug planning objective when compared to Rough Set method.",

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journal = "Procedia Computer Science",

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TY - JOUR

T1 - Dosage planning for diabetes patients using data mining methods

AU - Yildirim, Emirhan Gülçin

AU - Karahoca, Adem

AU - Uçar, Tamer

PY - 2011

Y1 - 2011

N2 - The condition of high blood sugar (glucose) level is called as diabetes mellitus. Cause of this disease can be either insufficient insulin production or improper response of body cell to insulin. Diabetes patients should use different drugs in order to keep their blood sugar level within normal range values. The purpose of this study is to develop a data mining model for which will predict a suitable dosage planning for diabetes patients. Medical records of 89 different patient records were used in this study. 318 diabetes assays were extracted using these patient records. ANFIS and Rough Set methods were used for dosage planning objective. According to the results of ANFIS and Rough Set methods, ANFIS is a more successful and reliable method for diabetes drug planning objective when compared to Rough Set method.

AB - The condition of high blood sugar (glucose) level is called as diabetes mellitus. Cause of this disease can be either insufficient insulin production or improper response of body cell to insulin. Diabetes patients should use different drugs in order to keep their blood sugar level within normal range values. The purpose of this study is to develop a data mining model for which will predict a suitable dosage planning for diabetes patients. Medical records of 89 different patient records were used in this study. 318 diabetes assays were extracted using these patient records. ANFIS and Rough Set methods were used for dosage planning objective. According to the results of ANFIS and Rough Set methods, ANFIS is a more successful and reliable method for diabetes drug planning objective when compared to Rough Set method.

KW - ANFIS

KW - Diabetes

KW - Dosage planning

KW - Rough set theory

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DO - 10.1016/j.procs.2011.01.018

M3 - Conference article

AN - SCOPUS:79952510961

SN - 1877-0509

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EP - 1380

JO - Procedia Computer Science

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T2 - 1st World Conference on Information Technology, WCIT-2010

Y2 - 6 October 2010 through 10 October 2010

ER -

Dosage planning for diabetes patients using data mining methods

Abstract

Keywords

UN SDGs

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