Automated Scoring of Narrative Recall Assessments Using Large Language Models Enables Exploration of Alternate Scoring Criteria

Abstract

Background: Clinical neuropsychological assessments, particularly narrative recall tests, present significant challenges for real‐time scoring due to the need for rapid interpretation. While post‐hoc scoring from recordings improves accuracy, time constraints in clinical settings often preclude this approach.