Exploring Links Between Psychosis and Frontotemporal Dementia Using Multimodal Machine Learning: Dementia Praecox Revisited.
Koutsouleris N, Pantelis C, Velakoulis D, McGuire P, Dwyer DB, Urquijo-Castro MF, Paul R, Dong S, Popovic D, Oeztuerk O, Kambeitz J, Salokangas RKR, Hietala J, Bertolino A, Brambilla P, Upthegrove R, Wood SJ, Lencer R, Borgwardt S, Maj C, Nöthen M, Degenhardt F, Polyakova M, Mueller K, Villringer A, Danek A, Fassbender K, Fliessbach K, Jahn H, Kornhuber J, Landwehrmeyer B, Anderl-Straub S, Prudlo J, Synofzik M, Wiltfang J, Riedl L, Diehl-Schmid J, Otto M, Meisenzahl E, Falkai P, Schroeter ML; International FTD-Genetics Consortium (IFGC), the German Frontotemporal Lobar Degeneration (FTLD) Consortium, and the PRONIA Consortium.
Koutsouleris N, et al.
JAMA Psychiatry. 2022 Sep 1;79(9):907-919. doi: 10.1001/jamapsychiatry.2022.2075.
JAMA Psychiatry. 2022.
PMID: 35921104
Free PMC article.
OBJECTIVE: To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant frontotemporal dementia (bvFTD), Alzheimer disease (AD), and schizophrenia; estimate predictability in patients with bvFTD and schizophrenia …
OBJECTIVE: To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant f …