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SMAS: Structural MRI-based AD Score using Bayesian supervised VAE

delete2025-08-15
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OA
AI
A
Aditya Nemali
J
José Bernal
R
Renat Yakupov
D
Devesh Singh
M
Martin Dyrba
E
Enise I. Incesoy
S
Soumya Mukherjee
O
Oliver Peters
E
Ersin Ersözlü
J
Julian Hellmann‐Regen
L
L. Preis
J
Josef Priller
E
Eike Jakob Spruth
S
Slawek Altenstein
A
Andrea Lohse
A
Anja Schneider
K
Klaus Fließbach
O
Okka Kimmich
J
Jens Wiltfang
N
Niels Hansen
B
Björn H. Schott
A
Ayoob Rostamzadeh
W
Wenzel Glanz
M
Michaela Butryn
K
Katharina Büerger
D
Daniel Janowitz
M
Michael Ewers
R
Robert Perneczky
B
Boris‐Stephan Rauchmann
S
Stefan Teipel
I
Ingo Kilimann
D
D. Goerss
C
Christoph Laske
S
Sebastian Sodenkamp
A
Annika Spottke
M
Marie Coenjaerts
F
Frederic Brosseron
F
Falk Lüsebrink
P
Peter Dechent
K
Klaus Scheffler
S
Stefan Hetzer
L
Luca Kleineidam
M
Mitchell Stark
F
F. Jessen
E
Emrah Düzel
G
Gabriel Ziegler
DOI:10.1016/j.compbiomed.2025.110829delete
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Abstract

Abstract

En 中文
• Structural MRI-based AD Score (SMAS) quantifies AD-specific morphometric patterns. • SMAS enables stratification and monitoring of individuals along the AD continuum. • SMAS outperforms both SPARE-AD and hippocampal volume across ADNI and DELCODE. • SMAS yields interpretable maps depicting regional contributions to the prediction.
Keywords:
Brain morphology indices
Bayesian Supervised Variational Autoencoder
Cognitive decline
Alzheimer’s disease
Bayesian inference

Journal

Computers in Biology and Medicine cover
Computers in Biology and Medicine
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6.3
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8.3K
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3.3W

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university of tübingen
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University of Cologne
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otto-von-guericke university (ovgu)
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University Hospital Bonn and University of Bonn
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