Author(s): Meenakshi K, Maragatham G

Email(s): meenakbalaji@gmail.com

DOI: 10.5958/0974-360X.2019.00669.3   

Address: Meenakshi K1, Maragatham G2
1SRM Institute of Science & Technology, Kancheepuram, Tamil Nadu, India, 603203
2SRM Institute of Science & Technology Kancheepuram, Tamil Nadu, India 603203
*Corresponding Author

Published In:   Volume - 12,      Issue - 8,     Year - 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.


Cite this article:
Meenakshi K, Maragatham G. Computational Intelligence in Diagnosis and Prognosis of Gestational Diabetes using Deep Learning. Research J. Pharm. and Tech 2019; 12(8):3891-3895. doi: 10.5958/0974-360X.2019.00669.3

Cite(Electronic):
Meenakshi K, Maragatham G. Computational Intelligence in Diagnosis and Prognosis of Gestational Diabetes using Deep Learning. Research J. Pharm. and Tech 2019; 12(8):3891-3895. doi: 10.5958/0974-360X.2019.00669.3   Available on: https://rjptonline.org/AbstractView.aspx?PID=2019-12-8-59


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RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

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