Predicting Brain Age at Slice Level: Convolutional Neural Networks and Consequences for Interpretability

Problem: Chronological aging in later life is associated with brain degeneration processes and increased risk for disease such as stroke and dementia. With a worldwide tendency of aging populations and increased longevity, mental health, and psychiatric research have paid increasing attention to und...

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Главные авторы:	Pedro L. Ballester, Laura Tomaz da Silva, Matheus Marcon, Nathalia Bianchini Esper, Benicio N. Frey, Augusto Buchweitz, Felipe Meneguzzi
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Frontiers Media S.A. 2021-02-01
Серии:	Frontiers in Psychiatry
Предметы:	brain age deep learning neuroimaging convolutional neural networks model interpretability
Online-ссылка:	https://www.frontiersin.org/articles/10.3389/fpsyt.2021.598518/full
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