Automating Rey Complex Figure Test scoring using a deep learning-based approach: a potential large-scale screening tool for cognitive decline.

Journal: Alzheimer's research & therapy
Published Date:

Abstract

BACKGROUND: The Rey Complex Figure Test (RCFT) has been widely used to evaluate the neurocognitive functions in various clinical groups with a broad range of ages. However, despite its usefulness, the scoring method is as complex as the figure. Such a complicated scoring system can lead to the risk of reducing the extent of agreement among raters. Although several attempts have been made to use RCFT in clinical settings in a digitalized format, little attention has been given to develop direct automatic scoring that is comparable to experienced psychologists. Therefore, we aimed to develop an artificial intelligence (AI) scoring system for RCFT using a deep learning (DL) algorithm and confirmed its validity.

Authors

  • Jun Young Park
    Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, South Korea.
  • Eun Hyun Seo
    Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, South Korea.
  • Hyung-Jun Yoon
    Department of Neuropsychiatry, College of Medicine, Chosun University, Gwangju, South Korea.
  • Sungho Won
    Department of Public Health Sciences, Seoul National University (Y.L., S.W.).
  • Kun Ho Lee
    National Research Center for Dementia, Chosun University, Gwangju, Republic of Korea.