1. Ktisis Cyprus University of Technology
  2. Cyprus University of Technology (Research Output)
  3. Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30046
DC FieldValueLanguage
dc.contributor.authorPrentzas, Nicoletta-
dc.contributor.authorNicolaides, Andrew N.-
dc.contributor.authorKyriacou, Efthyvoulos C.-
dc.contributor.authorKakas, Antonis-
dc.contributor.authorPattichis, Constantinos S.-
dc.date.accessioned2023-08-03T08:42:48Z-
dc.date.available2023-08-03T08:42:48Z-
dc.date.issued2019-10-28-
dc.identifier.citation19th International Conference on Bioinformatics and Bioengineering, BIBE 2019, Athens,28 - 30 October 2019en_US
dc.identifier.isbn9781728146171-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/30046-
dc.description.abstractDespite the recent recognition of the value of Artificial Intelligence and Machine Learning in healthcare, barriers to further adoption remain, mainly due to their 'black box' nature and the algorithm's inability to explain its results. In this paper we present and propose a methodology of applying argumentation on top of machine learning to build explainable AI (XAI) models. We compare our results with Random Forests and an SVM classifier that was considered best for the same dataset in [1].en_US
dc.language.isoenen_US
dc.rights© IEEEen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectArgumentationen_US
dc.subjectExplainabilityen_US
dc.subjectInTreesen_US
dc.subjectRandom forestsen_US
dc.subjectXAIen_US
dc.titleIntegrating machine learning with symbolic reasoning to build an explainable ai model for stroke predictionen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationFrederick Universityen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.relation.conferenceProceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019en_US
dc.identifier.doi10.1109/BIBE.2019.00152en_US
dc.identifier.scopus2-s2.0-85078574032-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85078574032-
cut.common.academicyear2019-2020en_US
dc.identifier.spage817en_US
dc.identifier.epage821en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.languageiso639-1en-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-4589-519X-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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