Model fit for in-sample and out-of-sample data.

<p>(A) Goodness of fit for four models, local FKPP, global FKPP, diffusion and logistic. For all panels, each point represents a region in the connectome model, averaged over subjects per scan. Top row shows estimated vs observed SUVR values. Bottom row shows estimated change vs observed chang...

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Bibliographic Details
Main Author:	Pavanjit Chaggar (9515394) (author)
Other Authors:	Jacob W. Vogel (17601848) (author), Alexa Pichet Binette (17282919) (author), Travis B. Thompson (9515391) (author), Olof Strandberg (5612342) (author), Niklas Mattsson-Carlgren (15238039) (author), Linda Karlsson (368463) (author), Erik Stomrud (371678) (author), Saad Jbabdi (117812) (author), Stefano Magon (513040) (author), Gregory Klein (4673425) (author), Oskar Hansson (233854) (author), Alain Goriely (1669849) (author)
Published:	2025
Subjects:	Genetics Molecular Biology Neuroscience Biotechnology Science Policy Mental Health Infectious Diseases Biological Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> aggregation two independent cohorts predict accurately subject new clinical tool alzheimer &# 8217 tau pet data pathological tau seeds hyperphosphorylated tau protein rich spatiotemporal pattern local tau production disease exhibiting transport pathologic tau spatiotemporal process local production transport dynamics sequentially progressing regional level potentially providing early stage disease timeline central driver brain regions accumulation exhibits
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Model fit for in-sample and out-of-sample data.

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