Medicine prediction based on doctor’s degree: a data mining approach

Md Shohel Arman, Kaushik Sarker, Asif Khan Shakir, Shah Fahad Hossain, Afia Hasan

Abstract


The effective use of information mining in profoundly unmistakable fields like e-business, promoting and retail has prompted its application in different enterprises. There is an absence of powerful investigation devices to find concealed connections and patterns in information. This examination paper expects to give a review of ebb and flow systems of learning revelation in databases utilizing information mining strategies that are being used in today’s therapeutic research especially in medicine prediction. Correlation, Chi-square and Euclidean distance feature selections are used to select features and showing the comparison of the result between K-Nearest neighbors, Naïve Bayes, decision tree, artificial neural network. The result uncovers that decision tree beats and sometime Bayesian grouping is having comparative precision as of choice tree. The analysis of performance can be done in such as doctor’s degrees may vary the diseases medicine.

Keywords


Data mining; Feature selection; Machine learning; Medicine prediction; Neural network

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DOI: http://doi.org/10.11591/ijeecs.v26.i2.pp1125-1134

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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