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• W4321107330 abstract "Multidisciplinary clinical decision-making has become increasingly important for complex diseases, such as cancers, as medicine has become very specialized. Multiagent systems (MASs) provide a suitable framework to support multidisciplinary decisions. In the past years, a number of agent-oriented approaches have been developed on the basis of argumentation models. However, very limited work has focused, thus far, on systematic support for argumentation in communication among multiple agents spanning various decision sites and holding varying beliefs. There is a need for an appropriate argumentation scheme and identification of recurring styles or patterns of multiagent argument linking to enable versatile multidisciplinary decision applications. We propose, in this paper, a method of linked argumentation graphs and three types of patterns corresponding to scenarios of agents changing the minds of others (argumentation) and their own (belief revision): the collaboration pattern, the negotiation pattern, and the persuasion pattern. This approach is demonstrated using a case study of breast cancer and lifelong recommendations, as the survival rates of diagnosed cancer patients are rising and comorbidity is the norm." @default.
• W4321107330 created "2023-02-17" @default.
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• W4321107330 date "2023-02-15" @default.
• W4321107330 modified "2023-09-26" @default.
• W4321107330 title "Linked Argumentation Graphs for Multidisciplinary Decision Support" @default.
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• W4321107330 doi "https://doi.org/10.3390/healthcare11040585" @default.
• W4321107330 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36833121" @default.
• W4321107330 hasPublicationYear "2023" @default.
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