부산대학교 도서관

Abstract Introduction The clock drawing task (CDT) is frequently used to aid in detecting cognitive impairment, but current scoring techniques are time‐consuming and miss relevant features, justifying the creation of an automated quantitative scoring approach. Methods We used computer vision methods to analyze the stored scanned images (N = 7,109), and an intelligent system was created to examine these files in a study of aging World Trade Center responders. Outcomes were CDT, Montreal Cognitive Assessment (MoCA) score, and incidence of mild cognitive impairment (MCI). Results The system accurately distinguished between previously scored CDTs in three CDT scoring categories: contour (accuracy = 92.2%), digits (accuracy = 89.1%), and clock hands (accuracy = 69.1%). The system reliably predicted MoCA score with CDT scores removed. Predictive analyses of the incidence of MCI at follow‐up outperformed human‐assigned CDT scores. Discussion We created an automated scoring method using scanned and stored CDTs that provided additional information that might not be considered in human scoring.