International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume4,March 2017,

Topic : A Proposal for Epidemic Prediction using Deep Learning

Authors:Sagar Palao || Abhishek Shahasane,Siddhesh Dighe, Harsh Gupta,Anjali Yeole

Abstract:HealthCare has been a surging need in India. The inception of Smart India, Smart Villages has further emphasized the need of a Smart & Healthy India. However little reflection of such digitally empowered country has been seen in the field of healthcare. This has further increased the importance of the definition of ubiquity of information and computing technology in healthcare that demand constant surveillance and vigilance of healthcare to predict epidemic outbreak and biological attack. The paper’s primary focus is to analyze and determine the spread of diseases and epidemic in cities/villages. And using this analysis to predict where the next outbreak of epidemic will be. This prediction helps the health authorities to take necessary action in terms of assuring that sufficient resources are available to suffice the need and if possible stop the occurrence of such epidemic by taking necessary actions. To achieve this, we use deep neural network as the heart of our prediction. It receives its training from the past experiences of data which we have collected from hospitals and our spread network. Using this training with our dynamic data it makes predictions as well as adaptively learns from the real time data..

Keywords: epidemic prediction, deep learning, recurrent neural network, machine learning, disease spread network

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DOI: 01.1617/vol4/iss3/pid01563


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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
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