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Intuitionistic Fuzzy PROMETHEE Method for Medical Ventilator Selection

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Micro-Electronics and Telecommunication Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 617))

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Abstract

Knowledge about medical ventilators is paramount as it acts as a lifesaver for COVID patients. Due to the availability of unrelated health conditions, the medical market manufactured numerous ventilators with unique features. This evaluation process aids in selecting the suitable ventilator for critical stage COVID patients. Multi-criteria decision-making processes are used to manage this selection. The pentagonal intuitionistic fuzzy set (PIFS) is utilized to deal with uncertain information because it incorporates both belongingness and non-belongingness grades, making it more precise than traditional fuzzy sets. This work combines the preference ranking organization method for enrichment evaluation (PROMETHEE) and PIFS for deciding the medical ventilator. The criteria are weighted through entropy technique. A new defuzzification approach is introduced for PIFS, and a case study involving ventilator assessment under a PIFS context is used to demonstrate the robustness of the proposed method. The attained result is validated by comparing with the extant fuzzy MCDM method. Therefore, this work aids medical professionals in selecting the best life-saving ventilators for COVID patients in the critical stage.

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Author information

Authors and Affiliations

  1. Mathematics Division, School of Advanced Sciences, Vellore Institute of Technology, Chennai, 606127, India

    S. Aicevarya Devi & A. Felix

Authors
  1. S. Aicevarya Devi
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  2. A. Felix
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Corresponding author

Correspondence to S. Aicevarya Devi .

Editor information

Editors and Affiliations

  1. SRM Institute of Science and Technology, Ghaziabad, India

    Devendra Kumar Sharma

  2. National Taipei University of Business, Hualien, Taiwan

    Sheng-Lung Peng

  3. SRM Institute of Science and Technology, Ghaziabad, Uttar Pradesh, India

    Rohit Sharma

  4. Department of Embedded Systems Engineering, College of Information Technology, Incheon National University, Incheon, Korea (Republic of)

    Gwanggil Jeon

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Aicevarya Devi, S., Felix, A. (2023). Intuitionistic Fuzzy PROMETHEE Method for Medical Ventilator Selection. In: Sharma, D.K., Peng, SL., Sharma, R., Jeon, G. (eds) Micro-Electronics and Telecommunication Engineering . Lecture Notes in Networks and Systems, vol 617. Springer, Singapore. https://doi.org/10.1007/978-981-19-9512-5_53

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  • DOI: https://doi.org/10.1007/978-981-19-9512-5_53

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-9511-8

  • Online ISBN: 978-981-19-9512-5

  • eBook Packages: EngineeringEngineering (R0)

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