Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures.

ABSTRACT: Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort

SUBMITTER: Yang Z 

PROVIDER: S-EPMC10793523 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature