Explainable automated evaluation of the clock drawing task for memory impairment screening

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.