IEEE Style Citation: Suhasini Vijaykumar, Manjiri Moghe, “Diabetes Prediction using Data Mining,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.749-753, 2019.
MLA Style Citation: Suhasini Vijaykumar, Manjiri Moghe "Diabetes Prediction using Data Mining." International Journal of Computer Sciences and Engineering 7.3 (2019): 749-753.
APA Style Citation: Suhasini Vijaykumar, Manjiri Moghe, (2019). Diabetes Prediction using Data Mining. International Journal of Computer Sciences and Engineering, 7(3), 749-753.
BibTex Style Citation:
@article{Vijaykumar_2019,
author = {Suhasini Vijaykumar, Manjiri Moghe},
title = {Diabetes Prediction using Data Mining},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {749-753},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3911},
doi = {https://doi.org/10.26438/ijcse/v7i3.749753}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.749753}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3911
TI - Diabetes Prediction using Data Mining
T2 - International Journal of Computer Sciences and Engineering
AU - Suhasini Vijaykumar, Manjiri Moghe
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 749-753
IS - 3
VL - 7
SN - 2347-2693
ER -
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Abstract
Data Mining is a way to extract information from large amount of data. It brings out one conclusion by applying its efficient techniques. In today’s world, it has helped many of the domains and growing its root by enhancing in its own way. In various data repositories, large medical datasets are available which are used in real world applications. Information is been generated by using various Data Mining techniques. Classification technique separates the information so as to generate useful content from it. It also helps in medical field to detect diseases such as diabetes which has affected various people from different countries. Insulin is main concept while taking into consideration the term ‘Diabetes’. Insulin acts as glucose for energy. It is a Gateway to body cells and controls glucose level in our body. Diabetes is a disease in which level of glucose in blood increases. To make it easy and recover from most early stages, prediction is necessary. It is been done with the help of data mining. This study is significant of predicting diabetes and helping medical industry to grow.
Key-Words / Index Term
Health, Decision Tree, Diabetes, Prediction
References
[1]. E.I.Mohamed, R.Linderm, G.Perriello,N.Daniele, S.J.Poppl, & A.DeLorenzo. “Predicting type 2 diabetes using an electronic nose based artificial neural network analysis,” Diabetes nutrition & metabolism, 15(4),215–221.202.
[2]. Frank, A. & Asuncion, A. (2010). UCI Machine Learning Irvine, CA: University of California, School of Information and Computer Science.
[3] Khyati K.Gandi, Prof. Nilesh B. Prajapati. ‘Study of Diabetes Prediction using Feature Selection and Classification’ International Journal of Engineering Research & Technology. Vol-3. Issue-2. Feb-2014
[4] T.monika Singh, Rajashekar shashtry ‘Prediction of Diabetes Using Probability Approach’ International Journal of Engineering Research & Technology. Vol-4. Issue-2. Feb-2017
[5] Data Mining Concepts and Techniques by Jiawei Han and Micheline Kamber [Book]
[6] Predicting Diabetes: Clinical, Biological, and Genetic Approaches
Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR)
[7] Priya B. Patel, Parth P. Shah, Himanshu D. Patel. ‘Analyze Data Mining Algorithms for Predicition of Diabetes’ International Journal of Engineering Development and Reseach. Vol-5. Issue-3. 2017.
[8] Marije Lamain – de Ruiter, Anneke Kwee, Christiana A. Naaktgeboren, Arie Franx, Karel G. M. Moons and Maria P. H. Koster ‘Prediction models for the risk of gestational diabetes: a systematic review’ Diagnostic and Prognostic Research 2017 1:3
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