The Sequence of Neutrosophic Soft Sets and a Decision-Making Problem in Medical Diagnosis

Bui, Quang-Thinh; Ngo, My-Phuong; Snåšel, Václav; Pedrycz, Witold; Vo, Bay

doi:10.1007/s40815-022-01257-4

Cited by 11 publications

(3 citation statements)

References 35 publications

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“…Following this work, multi-criteria group decision making using intuitionistic fuzzy numbers was applied in COVID-19 by Dutta and Borah [11]. In 2022, neutrosophic soft sets based decision making was proposed to make diagnostic decisions [4]. This work introduces the sequence of NS sets and its various operations with application in medical diagnosis.…”

Section: Related Workmentioning

confidence: 99%

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Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Kumar,

Sharma

2024

Preprint

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Multi-criteria decision making (MCDM) is introduced using trapezoidal vague numbers (TVNs) in medicine. Initially concepts of centroid and signed distance are generalized for TVNs. We also provide some desirable properties of the proposed distance measure. The decision making involves the medical diagnostic problem to reduce the vagueness and non-specificity from its environment. In this MCDM, each symptom is classified into some criteria. States of the patients, weights for the existing symptoms are assumed as vague point entries and relations of symptom criteria and diseases are considered using trapezoidal vague number entries. The usefulness of the developed approach is when it shows its capability and validity of the delivery. A numerical computation is illustrated with the whole procedure of the decision making. To show the capability and distinctness of the proposed methodology, a comparative discussion for outcomes is given with pre existing method. Present method coincides with existing fuzzy based method for the initial diagnosis while possibility differences for patient P1 and patient P2 range from 1–16.3% by the method based on existing traditionally fuzzy approach and in present approach these differences range from 2.15–7.46%. In the present approach, addition to the membership, another function called non membership is taken that contributes the upper bound of membership. Between these two memberships the hesitation part is dealt sophisticatedly. Also consideration of trapezoidal vague number as membership grade than the point estimation handles the blur cloud of association effectively.

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Section: Related Workmentioning

confidence: 99%

“…Some relevant work is given using vague sets. In 2000, Hong and Choi applied vague set theory to multi-criteria decision problems [4].In 2010, In 2003, Chen worked on reliability theory by applying vague set theory [14]. Pandey et al defined triangular vague number in different way and applied it in decision-making problem [23].…”

Section: Related Workmentioning

confidence: 99%

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Kumar,

Sharma

2024

Preprint

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“…Farhadinia developed a divergence-based medical decision-making process for COVID-19 diagnosis in a hesitant fuzzy environment [21]. A novel algorithm for the decision-making problem of neutrosophic soft sets was proposed and applied to medical diagnosis [22]. Considering FS theory's inherent difficulties and the inadequacy of the parametrization tool, Molodtsov put forward the concept of the soft set [23].…”

Section: Introductionmentioning

confidence: 99%

Group Decision-Making Method with Incomplete Intuitionistic Fuzzy Soft Information for Medical Diagnosis Model

Chen,

Liu

2024

Mathematics

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The medical diagnosis of many critical diseases is difficult as it usually requires the combined effort of several doctors. At this time, the process of medical diagnosis is actually a group decision-making (GDM) problem. In group medical diagnosis, considering doctors’ weight information and fusing the interaction relation of symptoms remain open issues. To address this problem, a group decision-making method for intuitionistic fuzzy soft environments is proposed for medical diagnosis because the intuitionistic fuzzy soft set (IFSS) integrates the advantages of the soft set and intuitionistic fuzzy set (IFS). Intuitionistic fuzzy soft weighted Muirhead mean operators are constructed by combining Einstein operations with the Muirhead mean (MM) operator, and some properties and results are revealed. A group medical diagnosis model with unknown doctor weight information and incomplete intuitionistic fuzzy soft information is proposed. Similarity measures of the intuitionistic fuzzy soft matrix (IFSM) given by the doctors are used to estimate the incomplete information. To take into account the advantages of objective weight and subjective weight, the combined weights of doctors are calculated based on the IFSMs’ similarity measure and doctors’ grades. The developed operators are then used to combine the evaluation information and handle the correlation of input arguments in the group medical diagnosis process. Finally, a numerical problem is selected to illustrate the superiority of the proposed approach compared to related methods. The combined weights are determined to overcome the shortcomings of the single-weight method to some extent. Meanwhile, the proposed method is more comprehensive, and can provide more flexible and reasonable choices for group medical diagnosis problems.

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A new approach to neutrosophic soft rough sets

2023

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The Sequence of Neutrosophic Soft Sets and a Decision-Making Problem in Medical Diagnosis

Cited by 11 publications

References 35 publications

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Group Decision-Making Method with Incomplete Intuitionistic Fuzzy Soft Information for Medical Diagnosis Model

A new approach to neutrosophic soft rough sets

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