Brain tumor prediction using naïve Bayes’ classifier and decision tree algorithms

  • Authors

    • Danda Shashank Reddy
    • Chinta Naga Harshitha
    • Carmel Mary Belinda
    2018-02-05
    https://doi.org/10.14419/ijet.v7i1.7.10634
  • Diagnosis, Treatment, Efficient, Prediction, Proposing

  • Abstract

    Now a day’s many advanced techniques are proposed in diagnosing the tumor in brain like magnetic resonance imaging, computer tomography scan, angiogram, spinal tap and biospy. Based on diagnosis it is easy to predict treatment. All of the types of brain tumor are officially reclassified by the World Health Organization. Brain tumors are of 120 types, almost each tumor is having same symptoms and it is difficult to predict treatment. For this regard we are proposing more accurate and efficient algorithm in predicting the type of brain tumor is Naïve Bayes’ classification and decision tree algorithm. The main focus is on solving tumor classification problem using these algorithms. Here the main goal is to show that the prediction through the decision tree algorithm is simple and easy than the Naïve Bayes’ algorithm.

  • References

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      Brain Tumor ppt. Dr.Walaa Nasr Lecturer of Medical-Surgical Nursing Department Second year 2012

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  • How to Cite

    Shashank Reddy, D., Naga Harshitha, C., & Mary Belinda, C. (2018). Brain tumor prediction using naïve Bayes’ classifier and decision tree algorithms. International Journal of Engineering & Technology, 7(1.7), 137-141. https://doi.org/10.14419/ijet.v7i1.7.10634

    Received date: 2018-03-26

    Accepted date: 2018-03-26

    Published date: 2018-02-05