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Statistics report
Apr. 2024
Submitted Papers : 80
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  Journal Paper


Paper Title :
An Overview on Inference Model Application to Detect Juvenile Diabetes in Given Diabetic Patients Data using Classification Techniques

Author :Aparna Vaidyanathan, Vasantha Kalyani David

Article Citation :Aparna Vaidyanathan ,Vasantha Kalyani David , (2020 ) " An Overview on Inference Model Application to Detect Juvenile Diabetes in Given Diabetic Patients Data using Classification Techniques " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 22-28, Volume-8,Issue-11

Abstract : The diagnosis of type1 diabetes (T1D) in juveniles has become a great concern in today‟s situation. Diabetes associations all over the world are performing various experimental procedures to identify the cause and reasons that developdiabetes in new born babies. The factors are still generic and with personalized factors are experimental and fluctuating. Unfortunately, the control of medication happens after detection of diabetes in juvenile. New born babies are also of great concern but due to lack of techniques and awareness we ignore them. This medication and control should be initiated in a very early stage. The causes are genetic and from parental influences. The new born baby and yet to be juvenile diabetic should be identified when it is in a stage to get influenced. The only relative care is to be taken by the parent-to-be. To identify juvenile diabetes before they are born with the parental factors is a tremendous area to explore. There are few research findings that pertain to young children with T1D are reviewed, there is a huge vacuum in understanding the potential clinical implications for new born babies who can be future potential juvenile diabetic. This paper discusses the influential factors that can be generated based on parent‟s health especially if the parent is gestational diabetic and with personalized factors. It also focuses on how the diabetes can influence the new born child with gestational parents. Keywords - Juvenile diabetes, data mining, Analytical model, influential factors, gestational diabetes, Decision tree Algorithms and Naïve Bayes algorithm.

Type : Research paper

Published : Volume-8,Issue-11


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-17620   View Here

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