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A three-way decision method with tolerance dominance relations in decision information systems
In recent years, various medical diagnosis problems have been addressed from the perspective of multi-attribute decision making. Among them, the three-way decision theory can provide a novel scheme to solve medical diagnosis issues under the framework of multi-attribute decision making via consideri...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702967/ https://www.ncbi.nlm.nih.gov/pubmed/36466766 http://dx.doi.org/10.1007/s10462-022-10311-4 |
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author | Wang, Wenjie Zhan, Jianming Ding, Weiping Wan, Shuping |
author_facet | Wang, Wenjie Zhan, Jianming Ding, Weiping Wan, Shuping |
author_sort | Wang, Wenjie |
collection | PubMed |
description | In recent years, various medical diagnosis problems have been addressed from the perspective of multi-attribute decision making. Among them, the three-way decision theory can provide a novel scheme to solve medical diagnosis issues under the framework of multi-attribute decision making via considering transforming relationships between loss functions and decision matrices. In this paper, we primarily explore a three-way decision method with tolerance dominance relations in ordered decision information systems. In existing three-way decision models, all objects can be divided into two states, we utilize decision attributes to obtain the set of two states in ordered decision information systems. Then, in order to improve the accuracy of patient classifications, the paper simultaneously considers the influence of loss and gain functions for each object, and uses loss and gain functions to obtain net profit functions as new measurement functions. Meanwhile, a class of three-way decisions in terms of multi-attribute decision making rules based on a tolerance dominance relation is established. In light of the proposed three-way decision method, we further construct a multi-attribute decision making method by using tolerance dominance relations and the constructed method is applied to a medical diagnosis issue of Lymphography. Finally, a comparison analysis and an experimental evaluation are performed to illustrate the feasibility and effectiveness of the presented methodology. |
format | Online Article Text |
id | pubmed-9702967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-97029672022-11-28 A three-way decision method with tolerance dominance relations in decision information systems Wang, Wenjie Zhan, Jianming Ding, Weiping Wan, Shuping Artif Intell Rev Article In recent years, various medical diagnosis problems have been addressed from the perspective of multi-attribute decision making. Among them, the three-way decision theory can provide a novel scheme to solve medical diagnosis issues under the framework of multi-attribute decision making via considering transforming relationships between loss functions and decision matrices. In this paper, we primarily explore a three-way decision method with tolerance dominance relations in ordered decision information systems. In existing three-way decision models, all objects can be divided into two states, we utilize decision attributes to obtain the set of two states in ordered decision information systems. Then, in order to improve the accuracy of patient classifications, the paper simultaneously considers the influence of loss and gain functions for each object, and uses loss and gain functions to obtain net profit functions as new measurement functions. Meanwhile, a class of three-way decisions in terms of multi-attribute decision making rules based on a tolerance dominance relation is established. In light of the proposed three-way decision method, we further construct a multi-attribute decision making method by using tolerance dominance relations and the constructed method is applied to a medical diagnosis issue of Lymphography. Finally, a comparison analysis and an experimental evaluation are performed to illustrate the feasibility and effectiveness of the presented methodology. Springer Netherlands 2022-11-25 2023 /pmc/articles/PMC9702967/ /pubmed/36466766 http://dx.doi.org/10.1007/s10462-022-10311-4 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Wang, Wenjie Zhan, Jianming Ding, Weiping Wan, Shuping A three-way decision method with tolerance dominance relations in decision information systems |
title | A three-way decision method with tolerance dominance relations in decision information systems |
title_full | A three-way decision method with tolerance dominance relations in decision information systems |
title_fullStr | A three-way decision method with tolerance dominance relations in decision information systems |
title_full_unstemmed | A three-way decision method with tolerance dominance relations in decision information systems |
title_short | A three-way decision method with tolerance dominance relations in decision information systems |
title_sort | three-way decision method with tolerance dominance relations in decision information systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702967/ https://www.ncbi.nlm.nih.gov/pubmed/36466766 http://dx.doi.org/10.1007/s10462-022-10311-4 |
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