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Fuzzy Logic in Healthcare

Fuzzy Logic in Healthcare

Güney Gürsel
Copyright: © 2015 |Pages: 29
ISBN13: 9781466672581|ISBN10: 1466672587|EISBN13: 9781466672598
DOI: 10.4018/978-1-4666-7258-1.ch022
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MLA

Gürsel, Güney. "Fuzzy Logic in Healthcare." Handbook of Research on Artificial Intelligence Techniques and Algorithms, edited by Pandian Vasant, IGI Global, 2015, pp. 679-707. https://doi.org/10.4018/978-1-4666-7258-1.ch022

APA

Gürsel, G. (2015). Fuzzy Logic in Healthcare. In P. Vasant (Ed.), Handbook of Research on Artificial Intelligence Techniques and Algorithms (pp. 679-707). IGI Global. https://doi.org/10.4018/978-1-4666-7258-1.ch022

Chicago

Gürsel, Güney. "Fuzzy Logic in Healthcare." In Handbook of Research on Artificial Intelligence Techniques and Algorithms, edited by Pandian Vasant, 679-707. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-7258-1.ch022

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Abstract

The medical decision-making process is fuzzy in its nature. The physician handles linguistic concepts in deciding the diagnosis and prognosis. The conversion from this fuzzy nature into crisp real world outcome causes the loss of precision. Fuzzy logic is a suitable way to provide the physician with the support he needs in handling linguistic concepts and get rid of the loss of precision. Fuzzy logic technologies are applied to each area of medicine, and they have been proven to be successful. The literature shows that the medical area has a great compatibility with fuzzy logic technology. Fuzzy cognitive maps, fuzzy expert systems, fuzzy medical image processing, fuzzy applications in information retrieval from medical databases, fuzzy medical data mining, and hybrid fuzzy applications are the common and most known fuzzy logic usage areas in the medical field. This chapter is a descriptive study that examines and explains the common fuzzy logic applications in the medical field after an introduction to fuzzy logic.

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