Experts has a new look! Let us know what you think of the updates.

Provide feedback
Home
Scholarly Works
Predicting Brain Age at Slice Level: Convolutional...
Journal article

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

Abstract

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 understanding brain-related changes of aging. Recent findings suggest there is a brain age gap (a difference between chronological age and brain age …

Authors

Ballester PL; da Silva LT; Marcon M; Esper NB; Frey BN; Buchweitz A; Meneguzzi F

Journal

Frontiers in Psychiatry, Vol. 12, ,

Publisher

Frontiers

DOI

10.3389/fpsyt.2021.598518

ISSN

1664-0640

Labels

Sustainable Development Goals (SDG)