University of Aberdeen logo

AURA - Aberdeen University Research Archive

 

A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews

Simple item page
dc.contributor.authorMoreno-Garcia, Carlos Francisco
dc.contributor.authorJayne, Chrisina
dc.contributor.authorElyan, Eyad
dc.contributor.authorAceves Martins, Magaly
dc.contributor.institutionUniversity of Aberdeen.Rowett Instituteen
dc.date.accessioned2023-01-24T16:11:01Z
dc.date.available2023-01-24T16:11:01Z
dc.date.issued2023-03
dc.description.statusPeer revieweden
dc.format.extent9
dc.format.extent913497
dc.identifier226586465
dc.identifierc91ab211-b923-4407-af25-0ee4ab276f06
dc.identifier85147128799
dc.identifier.citationMoreno-Garcia, C F, Jayne, C, Elyan, E & Aceves Martins, M 2023, 'A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews', Decision Analytics Journal, vol. 6, 100162. https://doi.org/10.1016/j.dajour.2023.100162en
dc.identifier.doi10.1016/j.dajour.2023.100162
dc.identifier.issn2772-6622
dc.identifier.otherORCID: /0000-0002-9441-142X/work/127304781
dc.identifier.otherORCID: /0000-0002-9441-142X/work/127304781
dc.identifier.urihttps://hdl.handle.net/2164/19890
dc.identifier.vol6en
dc.language.isoeng
dc.relation.ispartofDecision Analytics Journalen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subjectbladder canceren
dc.subjectearly detectionen
dc.subjectbiomarkersen
dc.subjectdiagnostic performanceen
dc.subjectprimary careen
dc.subjectcommunityen
dc.subjectR Medicine (General)en
dc.subjectSupplementary Dataen
dc.subject.lccR1en
dc.titleA novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviewsen
dc.typeJournal articleen

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
Moreno_Garcia_etal_DAJ_A_Novel_Application_VOR.pdf
Size:
892.09 KB
Format:
Adobe Portable Document Format
Download

Collections

All research