CFP last date
20 December 2024
Reseach Article

A Neural Network based Approach for the Diabetes Risk Estimation

by Deepti Jain, Divakar Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 73 - Number 10
Year of Publication: 2013
Authors: Deepti Jain, Divakar Singh
10.5120/12774-8467

Deepti Jain, Divakar Singh . A Neural Network based Approach for the Diabetes Risk Estimation. International Journal of Computer Applications. 73, 10 ( July 2013), 1-4. DOI=10.5120/12774-8467

@article{ 10.5120/12774-8467,
author = { Deepti Jain, Divakar Singh },
title = { A Neural Network based Approach for the Diabetes Risk Estimation },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 73 },
number = { 10 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume73/number10/12774-8467/ },
doi = { 10.5120/12774-8467 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:39:41.360503+05:30
%A Deepti Jain
%A Divakar Singh
%T A Neural Network based Approach for the Diabetes Risk Estimation
%J International Journal of Computer Applications
%@ 0975-8887
%V 73
%N 10
%P 1-4
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetes is one of the most common anddramatically increasing metabolic diseases causes the increase in blood sugar. The patient having high blood sugar either caused by the bodyfailure to produce enough insulin (type 1) or the cells failure to respond to the produced insulin (type 2). Since the present medication cannot cure it hence the only way is to estimate the risk of diabetes for each person and take precautions according to the risk factor. This paper presents a Feed forward neural network based approach for the estimation of diabetes risk which estimates the risk factor for any person on the basis of body characteristics (like weight,Bloodpressure etc. ).

References
  1. Muhammad AkmalSapon, Khadijah Ismail and SuehazlynZainudin "Prediction of Diabetes by using Artificial Neural Network",2011 International Conference on Circuits, System and Simulation IPCSIT vol. 7 (2011)
  2. Akkarapol Sa-ngasoongsong and JongsawasChongwatpol "An Analysis of Diabetes Risk Factors Using Data Mining Approach", Paper PH10-2012.
  3. B. Y. Baha, Bank, Yola and G. M. Wajiga" Artificial Neural Networks to Detect Risk Of Type 2 Diabetes", JORIND 10 (2), June, 2012.
  4. ZaritaZainuddin, Ong Pauline and CemalArdil "A Neural Network Approach in Predicting the Blood Glucose Level for Diabetic Patients", International Journal of Information and Mathematical Sciences 5:1 2009.
  5. ManaswiniPradhan, Dr. Ranjit Kumar Sahu "Predict the onset of diabetes disease using Artificial Neural Network (ANN)", International Journal of Computer Science & Emerging Technologies Volume 2, Issue 2, April 2011.
  6. DavarGiveki, Hamid Salimi, GholamRezaBahmanyar, YounesKhademian "Automatic Detection of Diabetes Diagnosis using Feature Weighted Support Vector Machines based on Mutual Information and Modified Cuckoo Search".
  7. Wei Yu, Tiebin Liu, Rodolfo Valdez, Marta Gwinn, Muin J Khoury" Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes", BMC Medical Informatics and Decision Making 2010.
  8. Shoback, edited by David G. Gardner, Dolores (2011). Greenspan's basic & clinical endocrinology (9th ed. ). New York: McGraw-Hill Medical. pp. Chapter 17. ISBN 0-07-162243-8
  9. Gary S Collins*, Susan Mallett, Omar Omar and Ly-Mee Yu "Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting", BMC Medicine 2011, 9:103.
  10. "Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study", BMJ 2012; 345 doi: http://dx. doi. org/10. 1136/bmj. e5900
Index Terms

Computer Science
Information Sciences

Keywords

Feed forward Neural Network (FFNN) Diabetes Risk Estimation