Machine Learning-Based Cognitive Assessment With The Autonomous Cognitive Examination: Randomized Controlled Trial.

Journal: Journal of medical Internet research
Published Date: Jul 30, 2025

Abstract

BACKGROUND: The rising prevalence of dementia necessitates a scalable solution to cognitive assessments. The Autonomous Cognitive Examination (ACoE) is a foundational cognitive test for the phenotyping of cognitive symptoms across the primary cognitive domains. However, while the ACoE has been internally validated, it has not been externally validated in a clinical population, and its ability to render accurate appraisals of cognition is unknown. Further, it is unclear if these phenotypic assessments are useful in clinical tasks such as screening patients with and those without impairments.

Authors

  • Calvin Howard
    Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road 1st Floor, Boston, MA, 02115, United States.
  • Amy Johnson
    Section of Neurology, Department of Internal Medicine, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada.
  • Sheena Baratono
    Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA, 02215, United States.
  • Katharina Faust
    Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Joseph Peedicail
    Section of Neurology, Department of Internal Medicine, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada.
  • Marcus Ng
    Department of Neurology, University of Manitoba, Winnipeg, Manitoba, Canada.

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