Hybrid technique for medical data classification using multi-layer perceptron with NB classifier

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Abstract

Medical data analysis gains more interest from the last decade due to its significance advantages. Medical data is a heterogeneous data, which is the combination of text data, numeric data and image data. For to analyze such heterogeneous data traditional data analysis mechanisms are inefficient. To handle this heterogeneous data deep learning is obvious choice. Deep learning is able to handle text, numeric and image data more efficiently than traditional data mining techniques. In this paper we proposed a deep learning based multilayer perceptron to analysis medical data. This method independently address the text data, image data and numerical data and combinable made medical data classification.

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Rao, T. S. S., & Battula, B. P. (2019). Hybrid technique for medical data classification using multi-layer perceptron with NB classifier. International Journal of Innovative Technology and Exploring Engineering, 8(12), 2627–2632. https://doi.org/10.35940/ijitee.K2179.1081219

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