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Reseach Article

An Approach for Recommendations in Self Management of Diabetes based on Expert System

by Baran Hashemi, Hossein Javidnia
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 14
Year of Publication: 2012
Authors: Baran Hashemi, Hossein Javidnia
10.5120/8487-2431

Baran Hashemi, Hossein Javidnia . An Approach for Recommendations in Self Management of Diabetes based on Expert System. International Journal of Computer Applications. 53, 14 ( September 2012), 6-12. DOI=10.5120/8487-2431

@article{ 10.5120/8487-2431,
author = { Baran Hashemi, Hossein Javidnia },
title = { An Approach for Recommendations in Self Management of Diabetes based on Expert System },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 14 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 6-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number14/8487-2431/ },
doi = { 10.5120/8487-2431 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:04.115528+05:30
%A Baran Hashemi
%A Hossein Javidnia
%T An Approach for Recommendations in Self Management of Diabetes based on Expert System
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 14
%P 6-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetes self-management education is of significant importance, since people with diabetes and their families provide 95% of their care themselves. Hyperglycemia and hypoglycemia are two of the most serious acute complications of diabetes. Making appropriate decision in these situations needs knowledge about normal blood glucose levels and related signs and symptoms. In this paper an expert system is proposed using Visual C# 2008, aiming at nutrition recommendations applicable in blood glucose self management. This expert system consists of 4 sections: Body weight and daily nutritional requirements assessment, Hypo- and hyperglycemia symptoms, Self-monitoring of Blood Glucose (SMBG) and Diabetes related disease. In comparison with the other expert systems invented to manage blood glucose level, this expert system includes different aspects of diabetes and is usable for both experts and diabetes patients.

References
  1. International Diabetes Federation 2011. http://www. idf. org/diabetesatlas/5e/the-global-burden.
  2. World Health Organization 2011. http://www. who. int/mediacentre/factsheets/fs312/en/2011.
  3. Norris SL, Engelgau MM, Narayan KMV. 2001 Effectiveness of self-management training in type 2 diabetes. A systematic review of randomized controlled trials. Diabetes Care 2001, 24:561-587.
  4. Perantie DC, Lim A, Wu J, Weaver P, Warren S L, Sadler M, White N H and Hershey T. 2008 Effects of prior hypoglycemia and hyperglycemia on cognition in children with type 1 diabetes mellitus. (Apr 2008), 9(2): 87-95.
  5. Goya A, Mehta S R, Díaz R, Gerstein H C, Afzal R, Xavier D, Liu L, Pais P and Yusuf S. 2009 Differential Clinical Outcomes Associated With Hypoglycemia and Hyperglycemia in Acute Myocardial Infarction (November 2009). doi: 10. 1161/CIRCULATIONAHA. 108. 837765.
  6. Jha S K 2012 Development of knowledge base expert system for natural treatment of diabetes disease. IJACSA 3(3).
  7. Abu-naser s, El-Hissi H, Abu-Rass M, El-Khozondar N. 2010. An expert system for endocrine diagnosisand treatments using JESS. Journal of artificial intelligence 3(4): 239-251.
  8. Lee C. 2011. A Fuzzy Expert System for Diabetes Decision Support Application. IEEE digital library (Feb. 2011), 139-153.
  9. Devi R E, Nagaveni N. 2010. Design methodology of a fuzzy knowledgebase system to predict the risk of diabetic nephropathy. International Journal of Computer Science Issues (September 2010), 7(5).
  10. Akter M, Uddin M S and Haque A. 2009. Diagnosis and management of diabetes mellitus through a knowledge-based system. 13th International Conference on Biomedical Engineering, 23(3) 1000-1003.
  11. Peters A N, Davidson M B. 1998. Application of a diabetes managed care program. Diabetes Care. (July 1998), 21(7).
  12. Rodbard D and Vigersky R A. 2011. Design of a decision support system to help clinicians manage glycemia in patients with type 2 diabetes mellitus. (March 2011). Journal of Diabetes Science and Technology, 5(2).
  13. Balas E A, Krishna S, Kretschmer R A, Cheek T R, Lobach D F and Boren S A. 2004. Computerized knowledge management in diabetes care. Medical Care (June 2004), 42(6).
  14. Yoon K -H, Kim H –S. 2007. A short message service by cellular phone in type 2 diabetic patients for 12 months. Elsevier Ireland Ltd.
  15. Kalpana M. 2011"Fuzzy Expert System for Diabetes using Fuzzy Verdict Mechanism", Int. J. Advanced Networking and Applications, 03(02):1128-1134.
  16. Campos-Delgado D U, Hernandez-Ordonez M, Femat R and Gordillo-Moscos. 2006. Fuzzy-based controller for glucose regulation in type-1 diabetic patients by subcutaneous route, IEEE Trans. Biomed. Eng (Nov 2006), 53(11):2201-2210.
  17. Turnin M G, Beddok R H, Clottes J P, Martini P F, Abadie R G, Buisson J C 1992. Telematic expert system diabeto. Diabetes Care (Feb 1992)15(2).
  18. Kovasznai G 2011. Developing an expert system for diet recommendation. IEEE International Symposium on Applied Computational Intelligence and Informatics (May 2011), 19–21.
  19. Peter J, Introduction to Expert Systems, Addison Wesley, p. 2, ISBN 978-0-201-87686-4. 1998 (3 ed. )
  20. School of Computer Science, Carnegie Mellon, Advanced Agent and Robotics Technology Lab.
  21. Centers for Disease Control (CDC) and Prevention: Overweight and obesity 2009, http://www. cdc. gov/obesity/.
  22. Deurenberg P, Deurenberg- Yap M. 2003. Validity of body composition methods across ethnic population groups. Acta Diabetol 40:246.
  23. American Diabetes Association (ADbA), 2011. Diagnosis and classification of diabetes mellitus (Position Statement), Diabetes Care 34(Suppl 1):S63, 2011a.
Index Terms

Computer Science
Information Sciences

Keywords

Diabetes recommendation Expert system Hyperglycemia Hypoglycemia