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dc.contributor.authorTolonen, Antti
dc.contributor.authorRhodius-Meester, Hanneke F M
dc.contributor.authorBruun, Marie
dc.contributor.authorKoikkalainen, Juha
dc.contributor.authorBarkhof, Frederik
dc.contributor.authorLemstra, Afina W
dc.contributor.authorKoene, Teddy
dc.contributor.authorScheltens, Philip
dc.contributor.authorTeunissen, Charlotte E
dc.contributor.authorTong, Tong
dc.contributor.authorGuerrero, Ricardo
dc.contributor.authorSchuh, Andreas
dc.contributor.authorLedig, Christian
dc.contributor.authorBaroni, Marta
dc.contributor.authorRueckert, Daniel
dc.contributor.authorSoininen, Hilkka
dc.contributor.authorRemes, Anne M
dc.contributor.authorWaldemar, Gunhild
dc.contributor.authorHasselbalch, Steen G
dc.contributor.authorMecocci, Patrizia
dc.contributor.authorvan der Flier, Wiesje M
dc.contributor.authorLotjönen, Jyrki
dc.date.accessioned2018-05-16T11:17:59Z
dc.date.available2018-05-16T11:17:59Z
dc.date.issued2018
dc.identifier.urihttps://erepo.uef.fi/handle/123456789/6608
dc.description.abstractClinical decision support systems (CDSSs) hold potential for the differential diagnosis of neurodegenerative diseases. We developed a novel CDSS, the PredictND tool, designed for differential diagnosis of different types of dementia. It combines information obtained from multiple diagnostic tests such as neuropsychological tests, MRI and cerebrospinal fluid samples. Here we evaluated how the classifier used in it performs in differentiating between controls with subjective cognitive decline, dementia due to Alzheimer’s disease, vascular dementia, frontotemporal lobar degeneration and dementia with Lewy bodies. We used the multiclass Disease State Index classifier, which is the classifier used by the PredictND tool, to differentiate between controls and patients with the four different types of dementia. The multiclass Disease State Index classifier is an extension of a previously developed two-class Disease State Index classifier. As the two-class Disease State Index classifier, the multiclass Disease State Index classifier also offers a visualization of its decision making process, which makes it especially suitable for medical decision support where interpretability of the results is highly important. A subset of the Amsterdam Dementia cohort, consisting of 504 patients (age 65 ± 8 years, 44% females) with data from neuropsychological tests, cerebrospinal fluid samples and both automatic and visual MRI quantifications, was used for the evaluation. The Disease State Index classifier was highly accurate in separating the five classes from each other (balanced accuracy 82.3%). Accuracy was highest for vascular dementia and lowest for dementia with Lewy bodies. For the 50% of patients for which the classifier was most confident on the classification the balanced accuracy was 93.6%. Data-driven CDSSs can be of aid in differential diagnosis in clinical practice. The decision support system tested in this study was highly accurate in separating the different dementias and controls from each other. In addition to the predicted class, it also provides a confidence measure for the classification.
dc.language.isoenglanti
dc.publisherFrontiers Media SA
dc.relation.ispartofseriesFrontiers in aging neuroscience
dc.relation.urihttp://dx.doi.org/10.3389/fnagi.2018.00111
dc.rightsCC BY http://creativecommons.org/licenses/by/4.0/
dc.subjectneurodegenerative diseases
dc.subjectclassification
dc.subjectdecision support
dc.subjectAlzheimer’s disease
dc.subjectfrontotemporal lobar degeneration
dc.subjectvascular dementia
dc.subjectdementia with Lewy bodies
dc.titleData-Driven Differential Diagnosis of Dementia Using Multiclass Disease State Index Classifier
dc.description.versionpublished version
dc.contributor.departmentSchool of Medicine / Clinical Medicine
uef.solecris.id54424231en
dc.type.publicationTieteelliset aikakauslehtiartikkelit
dc.rights.accessrights© Authors
dc.relation.doi10.3389/fnagi.2018.00111
dc.description.reviewstatuspeerReviewed
dc.relation.articlenumber111
dc.relation.issn1663-4365
dc.relation.volume10
dc.rights.accesslevelopenAccess
dc.type.okmA1
uef.solecris.openaccessOpen access -julkaisukanavassa ilmestynyt julkaisu


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