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dc.contributor.authorRye, Ingrid
dc.contributor.authorVik, Alexandra
dc.contributor.authorKocinski, Marek Michal
dc.contributor.authorLundervold, Alexander Selvikvåg
dc.contributor.authorLundervold, Astri J.
dc.date.accessioned2022-10-28T12:33:46Z
dc.date.available2022-10-28T12:33:46Z
dc.date.created2022-10-19T09:51:53Z
dc.date.issued2022
dc.identifier.issn2045-2322
dc.identifier.urihttps://hdl.handle.net/11250/3028894
dc.description.abstractPatients with Mild Cognitive Impairment (MCI) have an increased risk of Alzheimer’s disease (AD). Early identification of underlying neurodegenerative processes is essential to provide treatment before the disease is well established in the brain. Here we used longitudinal data from the ADNI database to investigate prediction of a trajectory towards AD in a group of patients defined as MCI at a baseline examination. One group remained stable over time (sMCI, n = 357) and one converted to AD (cAD, n = 321). By running two independent classification methods within a machine learning framework, with cognitive function, hippocampal volume and genetic APOE status as features, we obtained a cross-validation classification accuracy of about 70%. This level of accuracy was confirmed across different classification methods and validation procedures. Moreover, the sets of misclassified subjects had a large overlap between the two models. Impaired memory function was consistently found to be one of the core symptoms of MCI patients on a trajectory towards AD. The prediction above chance level shown in the present study should inspire further work to develop tools that can aid clinicians in making prognostic decisions.en_US
dc.language.isoengen_US
dc.publisherNatureen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titlePredicting conversion to Alzheimer’s disease in individuals with Mild Cognitive Impairment using clinically transferable featuresen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.source.articlenumber15566en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.1038/s41598-022-18805-5
dc.identifier.cristin2062617
dc.source.journalScientific Reportsen_US
dc.identifier.citationScientific Reports. 2022, 12, 15566.en_US
dc.source.volume12en_US


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