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Distance Similarity as a CBR Technique for Early Detection of Breast Cancer: An Egyptian Case Study

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Information Systems Design and Intelligent Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 340))

Abstract

Case-based reasoning as a concept covers almost a lot of technologies and techniques including knowledge management, artificial intelligence, machine learning techniques as well as database technology. The usage of all these technologies can easily aid in early detection of breast cancer as well as help other decision makers take the right decision on time and all the times. Of the main hot topics nowadays concerning executive managers and decision makers is measuring the similarity between objects. For better performance most organizations are in need on semantic similarity and similarity measures. This article presents mathematically different distance metrics used for measuring the binary similarity between quantitative data within cases. The case study represents a quantitative data of breast cancer patients within Faculty of medicine Cairo University. The experimental results show that the squared chord distance yields better with a 96.76 % without normalization that correlate more closely with human assessments compared to other distance measures used in this study.

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Author information

Authors and Affiliations

  1. Scientific Research Group in Egypt (SRGE), Cairo, Egypt

    Heba Ayeldeen, Osman Hegazy & Aboul Ella Hassanien

  2. Faculty of Computers and Information, Cairo University, Cairo, Egypt

    Aboul Ella Hassanien

  3. Department of Molecular Biology, Faculty of Medicine, Cairo University, Cairo, Egypt

    Olfat Shaker

Authors
  1. Heba Ayeldeen
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  2. Olfat Shaker
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  3. Osman Hegazy
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  4. Aboul Ella Hassanien
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Corresponding author

Correspondence to Heba Ayeldeen .

Editor information

Editors and Affiliations

  1. University of Kalyanai, Kalyanai, West Bengal, India

    J. K. Mandal

  2. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  3. Dean, Faculty of Engineering, Technology, University of Kalyani, Kalyani, West Bengal, India

    Manas Kumar Sanyal

  4. Engineering and Technological Studies, University of Kalyani, Kalyani, West Bengal, India

    Partha Pratim Sarkar

  5. Department Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    Anirban Mukhopadhyay

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Ayeldeen, H., Shaker, O., Hegazy, O., Hassanien, A.E. (2015). Distance Similarity as a CBR Technique for Early Detection of Breast Cancer: An Egyptian Case Study. In: Mandal, J., Satapathy, S., Kumar Sanyal, M., Sarkar, P., Mukhopadhyay, A. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 340. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2247-7_46

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  • DOI: https://doi.org/10.1007/978-81-322-2247-7_46

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2246-0

  • Online ISBN: 978-81-322-2247-7

  • eBook Packages: EngineeringEngineering (R0)

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