Normative Modeling Via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer’s Disease

Author:

Wang Xuetong1,Zhou Rong1,Zhao Kanhao2,Leow Alex3,Zhang Yu2,He Lifang1

Affiliation:

1. Lehigh University,Department of Computer Science and Engineering,PA,USA

2. Lehigh University,Department of Bioengineering,PA,USA

3. University of Illinois at Chicago,Department of Psychiatry,IL,USA

Publisher

IEEE

Reference12 articles.

1. Oasis-3: longitudinal neuroimaging, clinical, and cognitive dataset for normal aging and alzheimer disease;lamontagne;medRxiv,2019

2. Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech;kim;ICML PMLR,2021

3. Normative modelling using deep autoencoders: a multi-cohort study on mild cognitive impairment and alzheimer’s disease;pinaya;BioRxiv,2020

4. fMRIPrep: a robust preprocessing pipeline for functional MRI

5. Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large‐scale multi‐sample study

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