Automated versus human scoring of the Rey-Osterrieth Complex Figure Test: a rapid review

This review demonstrates that digital automated ROCFT scoring achieves accuracy and reliability compared to traditional clinician ratings, with well-designed systems occasionally surpassing human performance. Expected advances in artificial intelligence and automation could further enhance clinical neuropsychology into the 21st century. However, clinical implementation faces several constraints: heterogeneous training datasets, limited evidence of usefulness across disorders, and lack of independent validation. Automated scoring should thus augment, not replace, clinical judgement. To address these limitations, future research should strive to establish disorder-specific norms, conduct independent validation in real-world clinical settings, and develop human-in-the-loop pipelines that combine automated efficiency with clinical oversight. Responsible implementation will require explicit governance frameworks that regulate data use and sharing, address privacy and 'mental data' concerns. These advances would strengthen the evidence-base and utility for automated ROCFT scoring and support its responsible integration into neuropsychological practice.