Use of the Clock Drawing Test and the Rey-Osterrieth Complex Figure Test-copy with convolutional neural networks to predict cognitive impairment.

ABSTRACT:

Background

The Clock Drawing Test (CDT) and Rey-Osterrieth Complex Figure Test (RCFT) are widely used as a part of neuropsychological test batteries to assess cognitive function. Our objective was to confirm the prediction accuracies of the RCFT-copy and CDT for cognitive impairment (CI) using convolutional neural network algorithms as a screening tool.

Methods

The CDT and RCFT-copy data were obtained from patients aged 60-80 years who had more than 6 years of education. In total, 747 CDT and 980 RCFT-copy figures were utilized. Convolutional neural network algorithms using TensorFlow (ver. 2.3.0) on the Colab cloud platform ( www.colab.

Research

google.com ) were used for preprocessing and modeling. We measured the prediction accuracy of each drawing test 10 times us

SUBMITTER: Youn YC 

PROVIDER: S-EPMC8059231 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature