Open Access Journal

ISSN : 2394-2320 (Online)

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

Monthly Journal for Computer Science and Engineering

Open Access Journal

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

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

A Proposal for Epidemic Prediction using Deep Learning

Author : Sagar Palao 1 Abhishek Shahasane 2 Siddhesh Dighe 3 Harsh Gupta 4 Anjali Yeole 5

Date of Publication :14th March 2017

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.

Reference :

    1. R. Chakoumakos, "Predicting Outbreak Severity through Machine Learning on Disease Outbreak Reports", Stanford Web, 2010.
    2. Y. Zhang, W. Cheung and J. Liu, "A Unified Framework for Epidemic Prediction based on Poisson Regression", IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 11, pp. 2878-2892, 2015.
    3. V. Yu and L. Madoff, "ProMED-mail: An Early Warning System for Emerging Diseases", Clinical Infectious Diseases, vol. 39, no. 2, pp. 227-232, 2004.
    4. Online detection and quantification of epidemics. BioMed Central Ltd, 2007.
    5. VoroGraph: Visualization Tools for Epidemic Analysis - IBM", Researcher.watson.ibm.com, 2016. [Online]. Available: http://researcher.watson.ibm.com/researcher/view_group.p hp?id=5992. [Accessed: 28- Oct- 2016].
    6. Epi Info™ | CDC", Cdc.gov, 2016. [Online]. Available: http://www.cdc.gov/epiinfo/index.html. [Accessed: 28- Oct- 2016].
    7. "Programs - EcoHealth Alliance", EcoHealth Alliance, 2016. [Online]. Available: http://www.ecohealthalliance.org/programs. [Accessed: 28- Oct- 2016]
    8. "Espacenet - Home page", Worldwide.espacenet.com, 2016. [Online]. Available: https://worldwide.espacenet.com/. [Accessed: 28- Oct2016].
    9. "patft", Patft.uspto.gov, 2016. [Online]. Available:http://http://patft.uspto.gov/netahtml/PTO/index.html. [Accessed: 28- Oct- 2016].

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