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dc.contributor.authorElyan, Eyad
dc.contributor.authorHussain, A.
dc.contributor.authorSheikh, Aziz
dc.contributor.authorVuttpittayamongkol, Pattaramon
dc.contributor.authorHijazi, Karolin
dc.date.accessioned2022-08-17T11:24:01Z
dc.date.available2022-08-17T11:24:01Z
dc.date.issued2022
dc.identifier.citationElyan , E , Hussain , A , Sheikh , A , Vuttpittayamongkol , P & Hijazi , K 2022 , ' Antimicrobial Resistance and Machine Learning : Challenges and Opportunities ' , IEEE Access , vol. 10 , pp. 31561 - 31577 . https://doi.org/10.1109/ACCESS.2022.3160213en
dc.identifier.issn2169-3536
dc.identifier.otherPURE: 214851412
dc.identifier.otherPURE UUID: e197213f-65bc-44f9-88b3-12d9bbc2efc2
dc.identifier.otherScopus: 85126520655
dc.identifier.urihttps://hdl.handle.net/2164/19072
dc.descriptionACKNOWLEDGMENT The authors would like to thank Global Challenge Research Fund (GCRF) for supporting this worken
dc.format.extent17
dc.language.isoeng
dc.relation.ispartofIEEE Accessen
dc.rightsUnder a Creative Commons License https://creativecommons.org/licenses/by/4.0/en
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subjectAMRen
dc.subjectAntimicrobial resistanceen
dc.subjectMachine learningen
dc.subjectLMICsen
dc.subjectRK Dentistryen
dc.subject.lccRKen
dc.titleAntimicrobial Resistance and Machine Learning : Challenges and Opportunitiesen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Dental Educationen
dc.contributor.institutionUniversity of Aberdeen.Institute of Medical Sciencesen
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2022.3160213


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