Intuitionistic Fuzzy Approach for Predicting Maternal Outcomes

Chukwudi Obinna Nwokoro, Udoinyang G. Inyang (), Imo J. Eyoh () and Paul Augustine Ejegwa ()
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Chukwudi Obinna Nwokoro: University of Uyo, Department of Computer Science, Faculty of Science
Udoinyang G. Inyang: University of Uyo, Department of Computer Science, Faculty of Science
Imo J. Eyoh: University of Uyo, Department of Computer Science, Faculty of Science
Paul Augustine Ejegwa: Federal University of Agriculture

Chapter Chapter 18 in Fuzzy Optimization, Decision-making and Operations Research, 2023, pp 399-421 from Springer

Abstract: Abstract The problem of maternal complications is prevalent in developing nations. Every pregnant woman is entitled to good reproductive health to enhance safe delivery. In this work, we applied the intuitionistic fuzzy distance measure approach to predict maternal complications. A new approach of intuitionistic fuzzy distance is developed and characterized by certain theoretical results. Owing to the prevalence of maternal complications in developing nations, we deployed the developed intuitionistic fuzzy distance approach for the prediction of maternal complications to avoid maternal mortality during childbirth. From the method of Szmidt and Kacprzk, stillbirth took the lead with 0.91142, while the method of Ejegwa et al., UTI takes the lead with 0.9286 but with the new method, we obtained the following Stillbirth (0.99489), Preterm (0.99445), Miscarriage (0.99445), UT I(0.99401), Full-term (0.99279), Placentae Previa (0.99112), and Mortality (0.98135). However, stillbirth took the lead with 0.99489 compared to others, with a strong relationship with preterm and miscarriage. Also, there is an improved value in the probability results compared to the previous methods.

Keywords: Maternal outcomes; Reproductive health; Intuitionistic fuzzy distance measure; Intuitionistic fuzzy sets (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-35668-1_18

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DOI: 10.1007/978-3-031-35668-1_18

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