PENSIEVE-AI a brief cognitive test to detect cognitive impairment across diverse literacy

作者：Tau Ming Liew, Jessica Yi Hui Foo, Howard H. Yang, Sze Yan Tay, Way Inn Koay, King Fan Yip, Simon Kang Seng Ting, Kaavya Narasimhalu, Weishan Li, Congyuan Tan, Dan Luo, Rebecca Chong, Rachel Shong, Christopher Sia, Gerald Choon‐Huat Koh, Julian Thumboo · 发表于：Nature Communications · 年份：2025 · DOI：10.1038/s41467-025-58201-x · 被引用次数：9 · 研究领域：Dementia and Cognitive Impairment Research、Health, Environment, Cognitive Aging

Undiagnosed cognitive impairment is a pervasive global issue, often due to subtle nature of early symptoms, necessitating the use of brief cognitive tests for early detection. However, most brief tests are not scalable (requiring trained professionals), and are not designed for lower literacy groups (e.g. in underserved communities). Here, we developed PENSIEVE-AITM, a drawing-based digital test that is less dependent on literacy, and can be self-administered in <5 min. In a prospective study involving 1758 community-dwelling individuals aged 65 and older from Singapore (education range = 0–23 years), our deep-learning model showed excellent performance in detecting clinically-adjudicated mild cognitive impairment and dementia (AUC = 93%), comparable to traditional neuropsychological assessments (AUC = 94%, Pcomparison = 1.000). Results were consistent even across education subgroups. Being less dependent on literacy, PENSIEVE-AI holds promise for broader deployment in literacy-diverse populations similar to Singapore (e.g. some Asian and lower- and middle-income countries), potentially improving early detection and intervention of cognitive impairment. PENSIEVE-AI is a drawing-based, digital cognitive test that can be self-administered in <5 min. It matches traditional tests in detecting cognitive impairment and dementia, offering promise for early detection in literacy-diverse populations.