Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India

Research Article

An Analysis of blood donors and Hepatitis C patients by using big data techniques

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  • @INPROCEEDINGS{10.4108/eai.7-6-2021.2308658,
        author={M.  Sivachandran and Dr.T.  Krishnakumar},
        title={An Analysis of blood donors and Hepatitis C patients by using big data techniques},
        proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India},
        publisher={EAI},
        proceedings_a={I3CAC},
        year={2021},
        month={6},
        keywords={sgdtext simplelinearregression simplelogistic smo smoreg and votedperceptron},
        doi={10.4108/eai.7-6-2021.2308658}
    }
    
  • M. Sivachandran
    Dr.T. Krishnakumar
    Year: 2021
    An Analysis of blood donors and Hepatitis C patients by using big data techniques
    I3CAC
    EAI
    DOI: 10.4108/eai.7-6-2021.2308658
M. Sivachandran1,*, Dr.T. Krishnakumar2
  • 1: Research Scholar, Department of CSE, Bharath Institute of Higher Education and Research, Chennai, India
  • 2: Professor, Department of CSE, Bharath Institute of Higher Education and Research, Chennai, India.
*Contact email: sivachandranm08@gmail.com

Abstract

The system focuses and produces the optimal solution. Such as the SGD Text approach gives the highest and optimal result such as 88.38% compare with other models. and Simple Linear Regression approach gives very lowest result compare with other models. SGD Text approach produces highest precision value level which is 82.61% compare with other models, The lowest precision value is 60.02% which is produced by Simple Linear Regression approach, the highest precision value is 81.19% which is SGD Text approach. The Simple Linear Regression, SMOreg and SMO and have respectively 0.21,0.23 and 0.25 seconds to build the model. Fast and exact clinical screening is essential for the fruitful treatment of infections. Utilizing AI calculations and dependent on research center blood test results. This information extends the model's utility for use by broad professionals and demonstrates that blood test results contain more data than doctors for the most part perceive.