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Nature Inspired Computing pp 49–53Cite as

Alternate Procedure for the Diagnosis of Malaria via Intuitionistic Fuzzy Sets

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 652))

Abstract

Malaria is a disease, which affects many people around the globe. In this study, we propose a fuzzy diagnosis approach for the clinical diagnosis of the type of malaria which affects the patient. By the help of the prescribed method, one can easily diagnose the type of malaria, without conducting any laboratory test. On the basis of relation between symptoms and various types of infection present in patients, we develop hypothetical medical information-based case study of patients with assigned degree of membership, non-membership, and intuitionistic index. By using the procedure, we can easily diagnose the type of malaria; for example, patient p 1 is suffering from Plasmodium malariae (Pm), p 2 is suffering from Plasmodium ovale (Po), p 3 is suffering from Plasmodium falciparum (Pf), and p 4 is suffering from Plasmodium vivax (Pv) and P. malariae (Pm). Also, we can develop a computer program for the proposed procedure.

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Authors and Affiliations

  1. Department of Mathematics, Faculty of Engineering, Manav Rachna International University, Faridabad, India

    Vijay Kumar & Sarika Jain

Authors
  1. Vijay Kumar
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  2. Sarika Jain
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Corresponding author

Correspondence to Vijay Kumar .

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Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, Delhi, India

    Bijaya Ketan Panigrahi

  2. Bharati Vidyapeeth’s Institute of Computer Applications and Management, New Delhi, Delhi, India

    M. N. Hoda

  3. Department of Computer Science and IT, University of Jammu, Jammu, Jammu and Kashmir, India

    Vinod Sharma

  4. Bharati Vidyapeeth’s Institute of Computer Applications and Management, New Delhi, Delhi, India

    Shivendra Goel

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Kumar, V., Jain, S. (2018). Alternate Procedure for the Diagnosis of Malaria via Intuitionistic Fuzzy Sets. In: Panigrahi, B., Hoda, M., Sharma, V., Goel, S. (eds) Nature Inspired Computing. Advances in Intelligent Systems and Computing, vol 652. Springer, Singapore. https://doi.org/10.1007/978-981-10-6747-1_6

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  • DOI: https://doi.org/10.1007/978-981-10-6747-1_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6746-4

  • Online ISBN: 978-981-10-6747-1

  • eBook Packages: EngineeringEngineering (R0)

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