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dc.creatorDaskalopulu A., Tsoukalas E., Bargiotas D.en
dc.date.accessioned2023-01-31T07:51:28Z
dc.date.available2023-01-31T07:51:28Z
dc.date.issued2019
dc.identifier10.1109/BIBE.2019.00109
dc.identifier.isbn9781728146171
dc.identifier.urihttp://hdl.handle.net/11615/73113
dc.description.abstractNormative and fuzzy aspects of Medical AI are examined and a framework is presented for the purpose of designing architectures that can accommodate the lifelong growth of data and knowledge pertaining to an individual's health, together with relevant privileges and permissions for access, growth and utilization of such a system. Considering disease through the normativistic perspective advanced by Sadegh-Zadeh, an action-theoretical analysis is adopted suitable for Medical AI. In this approach diseases are viewed as social artifacts mapped into deontic constructs. In a sense, they are action provoking states of affairs amenable to fuzzy computational approaches that in the past have found broad applicability to industrial process control. © 2019 IEEE.en
dc.language.isoenen
dc.sourceProceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85078575104&doi=10.1109%2fBIBE.2019.00109&partnerID=40&md5=d164827b535a6441f2e1d104eb36a073
dc.subjectBioinformaticsen
dc.subjectAction theoryen
dc.subjectComputational approachen
dc.subjectDeonticen
dc.subjectDeontic Logicen
dc.subjectIndustrial process controlen
dc.subjectKnowledge pertainingen
dc.subjectFuzzy logicen
dc.subjectInstitute of Electrical and Electronics Engineers Inc.en
dc.titleNormative and fuzzy aspects of medical AIen
dc.typeconferenceItemen


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