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  Published Paper Details:

  Paper Title

AI-Powered Epidemic Forecasting: A Machine Learning Approach to Disease Surveillance

  Authors

  Priyanka Lokhande,  Santosh Gaikwad,  Arshiya Khan,  R.S. Deshpande

  Keywords

Machine learning, epidemic forecasting, infectious disease surveillance, deep learning, outbreak prediction, real-time analytics, federated learning, explainable AI, public health, IoT health monitoring.

  Abstract


This paper explores how machine learning enhances epidemic forecasting by leveraging multimodal data for accurate, real-time outbreak prediction. It also addresses implementation challenges and proposes a modular, ethical AI-based surveillance framework

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2506534

  Paper ID - 289118

  Page Number(s) - e609-e614

  Pubished in - Volume 13 | Issue 6 | June 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Priyanka Lokhande,  Santosh Gaikwad,  Arshiya Khan,  R.S. Deshpande,   "AI-Powered Epidemic Forecasting: A Machine Learning Approach to Disease Surveillance", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 6, pp.e609-e614, June 2025, Available at :http://www.ijcrt.org/papers/IJCRT2506534.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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