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A Prospective Cohort Study to Develop and Validate a Multivariable Prediction Model for Transient Ischaemic Attack (TIA) Diagnosis Using Proteomic Discovery and Candidate Lipid Mass Spectrometry, Neuroimaging and Machine Learning: Study Protocol

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dc.contributor.authorMilton, A.G.
dc.contributor.authorKremer, K.L.
dc.contributor.authorRao, S.R.
dc.contributor.authorMas, E.
dc.contributor.authorSnel, M.F.
dc.contributor.authorTrim, P.J.
dc.contributor.authorEdwards, S.
dc.contributor.authorLau, S.
dc.contributor.authorJenkinson, M.
dc.contributor.authorNoschka, E.
dc.contributor.authorKoblar, S.A.
dc.contributor.authorHamilton-Bruce, M.A.
dc.contributor.conferenceAnnual Conference of the Asia Pacific Stroke Organization (APSO) (4 Dec 2020 - 6 Dec 2020 : Korea)
dc.date.issued2020
dc.description.statementofresponsibilityA.G Milton, K.L Kremer, S.R Rao, E Mas, M.F Snel, P.J Trim, S Edwards, S Lau, M Jenkinson, E Noschka, S.A Koblar, M.A Hamilton-Bruce
dc.identifier.citationCerebrovascular Diseases, 2020, vol.49, iss.Suppl. 1, pp.72-72
dc.identifier.doi10.1159/000513113
dc.identifier.isbn9783318068894
dc.identifier.issn1015-9770
dc.identifier.issn1421-9786
dc.identifier.orcidSnel, M.F. [0000-0002-8502-7274]
dc.identifier.orcidTrim, P.J. [0000-0001-8734-3433]
dc.identifier.orcidEdwards, S. [0000-0003-2074-1685]
dc.identifier.orcidLau, S. [0000-0002-5952-0516]
dc.identifier.orcidJenkinson, M. [0000-0001-6043-0166]
dc.identifier.orcidNoschka, E. [0000-0002-6058-3549]
dc.identifier.orcidKoblar, S.A. [0000-0002-8667-203X]
dc.identifier.orcidHamilton-Bruce, M.A. [0000-0002-5222-620X]
dc.identifier.urihttps://hdl.handle.net/2440/135831
dc.language.isoen
dc.publisherKarger
dc.rights© Copyright 2020 by S. Karger AG
dc.source.urihttp://karger.com/
dc.subjectNeurosciences and Neurology; Cardiovascular System and Cardiology
dc.titleA Prospective Cohort Study to Develop and Validate a Multivariable Prediction Model for Transient Ischaemic Attack (TIA) Diagnosis Using Proteomic Discovery and Candidate Lipid Mass Spectrometry, Neuroimaging and Machine Learning: Study Protocol
dc.typeConference paper
pubs.publication-statusPublished

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