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<p>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-AI<sup>TM</sup>, a drawing-based digital test that is less dependent on literacy, and can be self-administered in &lt;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%, <i>P</i><sub><i>comparison</i></sub> = 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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月23日

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  • Tau Ming Liew,
  • Jessica Yi Hui Foo,
  • Howard Yang,
  • Sze Yan Tay,
  • Way Inn Koay,
  • King Fan Yip,
  • Simon Kang Seng Ting,
  • Kaavya Narasimhalu,
  • Weishan Li,
  • Congyuan Tan,
  • Danlin Luo,
  • Rebecca Chong,
  • Rachel Shong,
  • Christopher Sia,
  • Gerald Choon-Huat Koh,
  • Julian Thumboo

摘要

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.