Data-driven multivariate identification of gyrification patterns in a transdiagnostic patient cohort: A cluster analysis approach

Background: Multivariate data-driven statistical approaches offer the opportunity to study multi-dimensional interdependences between a large set of biological parameters, such as high-dimensional brain imaging data. For gyrification, a putative marker of early neurodevelopment, direct comparisons o...

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Main Authors: Pfarr, Julia-Katharina, Meller, Tina, Brosch, Katharina, Stein, Frederike, Thomas-Odenthal, Florian, Evermann, Ulrika, Wroblewski, Adrian, Ringwald, Kai G., Hahn, Tim, Meinert, Susanne, Winter, Alexandra, Thiel, Katharina, Flinkenflügel, Kira, Jansen, Andreas, Krug, Axel, Dannlowski, Udo, Kircher, Tilo, Gaser, Christian, Nenadi´c, Igor
Format: Article
Language:English
Published: Philipps-Universität Marburg 2023
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Call Number: urn:nbn:de:hebis:04-es2024-07620
Publication Date: 2024-01-22
Source: Erstveröffentlichung: Pfarr JK, Meller T, Brosch K, Stein F, Thomas-Odenthal F, Evermann U, Wroblewski A, Ringwald KG, Hahn T, Meinert S, Winter A, Thiel K, Flinkenflügel K, Jansen A, Krug A, Dannlowski U, Kircher T, Gaser C, Nenadić I. Data-driven multivariate identification of gyrification patterns in a transdiagnostic patient cohort: A cluster analysis approach. Neuroimage. 2023 Nov 1;281:120349. https://doi.org/10.1016/j.neuroimage.2023.120349
Downloads: 34 (2024)
License: https://creativecommons.org/licenses/by-nc-nd/4.0/
Access URL: https://archiv.ub.uni-marburg.de/es/2024/0762
https://doi.org/10.1016/j.neuroimage.2023.120349