Acute Stage of Brain Stroke Diagnosis Using Hybrid Genetic Algorithm for Optimization of Feature Selection and Classifier

  • Authors

    • C Amuthadevi
    • K Meena
    • K Arthi
    2018-03-10
    https://doi.org/10.14419/ijet.v7i2.4.11168
  • Brain stroke diagnosis, MLP, Hybrid genetic algorithm,

  • Abstract

    Brain Stroke is the third leading reason of death or major disabilities and needs computer guided assistance to diagnose at an earliest stage of disease. Stroke results in great physical functioning restrictions, which negatively impacts the quality of life for survivors and also care givers. MRI of brain is mainly used for accurate diagnosis even though its cost is high. In this work, a Hybrid Genetic Algorithm (HGA) is proposed for feature selection with Independent Component analysis and parameters optimization of Multi layer Perceptron (MLP). The classification results are compared with simple KNN and MLP Classifiers.

     

     

  • References

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  • How to Cite

    Amuthadevi, C., Meena, K., & Arthi, K. (2018). Acute Stage of Brain Stroke Diagnosis Using Hybrid Genetic Algorithm for Optimization of Feature Selection and Classifier. International Journal of Engineering & Technology, 7(2.4), 70-75. https://doi.org/10.14419/ijet.v7i2.4.11168

    Received date: 2018-04-06

    Accepted date: 2018-04-06

    Published date: 2018-03-10