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Statistical Procedures for Fuzzy Data in Medical Research

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Fuzziness and Medicine: Philosophical Reflections and Application Systems in Health Care

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 302))

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Abstract

In medical research, there has been an increasing interest in statistical analysis of inherently imprecise, uncertain, or linguistic observations such as perceived breathlessness, general fatigue, or self images. Fuzzy sets can effectively encode them, and a variety of statistical procedures have been developed to analyze fuzzy data. In this paper, we review some of the procedures and explain how they can be applied to medical research.

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Author information

Authors and Affiliations

  1. The Johns Hopkins University, Baltimore, Maryland, USA

    Takehiko Nakama

Authors
  1. Takehiko Nakama
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Editors and Affiliations

  1. Edificio de Investigación, European Centre for Soft Computing, C Gonzalo Gutiérrez Quirós S/N, Mieres (Asturias), 33600, Spain

    Rudolf Seising

  2. , Department of Matematics and Informatics, Università di Palermo, Via Archirafi, 34, Palermo, 90123, Italy

    Marco Elio Tabacchi

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Nakama, T. (2013). Statistical Procedures for Fuzzy Data in Medical Research. In: Seising, R., Tabacchi, M. (eds) Fuzziness and Medicine: Philosophical Reflections and Application Systems in Health Care. Studies in Fuzziness and Soft Computing, vol 302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36527-0_19

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  • DOI: https://doi.org/10.1007/978-3-642-36527-0_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36526-3

  • Online ISBN: 978-3-642-36527-0

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