Modeling Brain Volume Using Deep Learning-Based Physical Activity Features in Patients With Dementia.

ABSTRACT: There is a proven correlation between the severity of dementia and reduced brain volumes. Several studies have attempted to use activity data to estimate brain volume as a means of detecting reduction early; however, raw activity data are not directly interpretable and are unstructured, making them challenging to utilize. Furthermore, in the previous research, brain volume estimates were limited to total brain volume and the investigators were unable to detect reductions in specific regions of the brain that are typically used to characterize disease progression. We aimed to evaluate volume prediction of 116 brain regions through activity data obtained combining time-frequency domain- and unsupervised deep learning-based feature extraction methods. We developed a feature extraction model b

SUBMITTER: Park B 

PROVIDER: S-EPMC8959707 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature