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Research Journal of Pharmacy and Technology
Year : 2019, Volume : 12, Issue : 8
First page : ( 3891) Last page : ( 3895)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2019.00669.3

Computational Intelligence in Diagnosis and Prognosis of Gestational Diabetes using Deep Learning

Meenakshi K*, Maragatham G

Department of IT, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Potheri, India, 603203

*Corresponding Author E-mail: meenakbalaji@gmail.com

Online published on 24 December, 2019.

Abstract

The medicinal and the computational field have an intrinsic connection, both the fields have been complementing to each other's growth. Diabetes is a life-threatening disease and one such type of it is gestational diabetes which usually occurs in women during pregnancy due to low insulin levels but usually disappears after pregnancy. SKLearn is a powerful computational tool used for machine learning and to amplify the computational power and simplify the process we have used Keras interface. This model has 1000 neurons and predicts if the women will have diabetes post pregnancy.

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Keywords

Convolutional Neural Network, Gestational Diabetes, Machine Learning.

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