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Related Experiment Video

Updated: Jun 26, 2026

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

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Published on: May 5, 2015

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

Calvin Howard^1,2,3,4, Amy Johnson⁵, Sheena Baratono^1,2

¹Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA, 02215, United States.

Journal of Medical Internet Research

|July 30, 2025

Summary

The Autonomous Cognitive Examination (ACoE) reliably assesses cognitive function and can screen patients, similar to traditional tests. This digital tool offers a scalable solution for cognitive phenotyping in clinical settings.

Keywords:

ACoE ML attention autonomous cognitive examination cognition cognitive assessment cognitive examination cognitive test dementia fluency language machine learning memory neurology neuropsychology visuospatial function

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Published on: September 27, 2020

Area of Science:

Neurology
Cognitive Science
Digital Health

Background:

Rising dementia prevalence requires scalable cognitive assessment solutions.
The Autonomous Cognitive Examination (ACoE) is a foundational tool for cognitive symptom phenotyping.
External validation of ACoE in clinical populations and its screening utility are currently unknown.

Purpose of the Study:

To externally validate the Autonomous Cognitive Examination (ACoE) for reliable cognitive phenotyping.
To assess the ACoE's efficacy as a screening tool compared to standard paper-based cognitive tests.

Main Methods:

A randomized crossover study involved 46 neurological patients comparing ACoE to paper-based tests (ACE-3 or MoCA).
Evaluated interrater reliability for overall and domain-specific cognitive scores.
Assessed ACoE's ability to classify patients similarly to established cognitive assessments.

Main Results:

ACoE demonstrated high interrater reliability for overall cognitive scores (ICC=0.89) and specific domains (Attention: ICC=0.74, Language: ICC=0.89, Memory: ICC=0.91, Fluency: ICC=0.74, Visuospatial: ICC=0.78).
ACoE effectively screened patients, achieving high diagnostic similarity to paper-based tests (AUC=0.96).

Conclusions:

The Autonomous Cognitive Examination (ACoE) reliably phenotypes cognitive symptoms in patients.
ACoE is effective for screening patients with cognitive impairments.
Future applications may include diagnosing specific cognitive etiologies.