Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/68827

TítuloGoal-Driven Structured Argumentation for Patient Management in a Multimorbidity Setting
Autor(es)Oliveira, Tiago
Dauphin, Jérémie
Satoh, Ken
Tsumoto, Shusaku
Novais, Paulo
Data2020
EditoraSpringer
RevistaLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resumo(s)We use computational argumentation to both analyse and generate solutions for reasoning in multimorbidity about consistent recommendations, according to different patient-centric goals. Reasoning in this setting carries a complexity related to the multiple variables involved. These variables reflect the co-existing health conditions that should be considered when defining a proper therapy. However, current Clinical Decision Support Systems (CDSSs) are not equipped to deal with such a situation. They do not go beyond the straightforward application of the rules that build their knowledge base and simple interpretation of Computer-Interpretable Guidelines (CIGs). We provide a computational argumentation system equipped with goal-seeking mechanisms to combine independently generated recommendations, with the ability to resolve conflicts and generate explanations for its results. We also discuss its advantages over and relation to Multiple-criteria Decision-making (MCDM) in this particular setting.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/68827
ISBN9783030446376
DOI10.1007/978-3-030-44638-3_11
ISSN0302-9743
Versão da editorahttps://link.springer.com/chapter/10.1007%2F978-3-030-44638-3_11
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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