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A Predictive Analysis on Medical Data Based on Outlier Detection Method Using Non-Reduct Computation

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Advanced Data Mining and Applications (ADMA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5678))

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Abstract

In this research, a new method to predict and diagnose medical dataset is discovered based on outlier mining method using Rough Sets Theory (RST). The RST is used to generate medical rules, while outliers are detected from the rules to diagnose the abnormal data. In detecting outliers, a computation of set of attributes or known as Non-Reduct is proposed by proposing two new formula of Indiscernibility Matrix Modula(iDMM D) and Indiscernibility Function Modulo (iDMFM D) based on RST. The results show that the proposed method is a fast detection method with lower detection rate. In conclusion, the computation of the Non-Reduct is expected to give medical knowledge that able to predict abnormality in dataset that could be used in medical analysis.

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Author information

Authors and Affiliations

  1. Polytechnic Sultan Idris Shah, Polytechnics Malaysia, Ministry of Higher Education, Sungai Lang, 45100, Sungai Air Tawar, Selangor, DE

    Faizah Shaari

  2. Center of Artificial Intelligence Technology, Faculty of Information Science and Technology, National University of Malaysia, 43600, Bangi, Selangor, DE

    Azuraliza Abu Bakar & Abdul Razak Hamdan

Authors
  1. Faizah Shaari
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  2. Azuraliza Abu Bakar
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  3. Abdul Razak Hamdan
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Editor information

Editors and Affiliations

  1. Knowledge Science & Engineering Institute, School of Education Technology, Beijing Normal University, Xinjiekouwai Ave. 19, 100875, Beijing, China

    Ronghuai Huang

  2. The Hong Kong University of Science and Technology, Clear Water Bay,, Hong Kong, Hong Kong

    Qiang Yang

  3. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  4. Faculty of Economics, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    João Gama

  5. School of Information, Zhongguancum, Renmin University, 100872, Beijing, China

    Xiaofeng Meng

  6. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, St. Lucia, Queensland, Australia

    Xue Li

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© 2009 Springer-Verlag Berlin Heidelberg

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Shaari, F., Bakar, A.A., Hamdan, A.R. (2009). A Predictive Analysis on Medical Data Based on Outlier Detection Method Using Non-Reduct Computation. In: Huang, R., Yang, Q., Pei, J., Gama, J., Meng, X., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2009. Lecture Notes in Computer Science(), vol 5678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03348-3_62

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  • DOI: https://doi.org/10.1007/978-3-642-03348-3_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03347-6

  • Online ISBN: 978-3-642-03348-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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