Scalable diagnostic screening of mild cognitive impairment using AI dialogue agent. Academic Article uri icon

Overview

abstract

  • The search for early biomarkers of mild cognitive impairment (MCI) has been central to the Alzheimer's Disease (AD) and dementia research community in recent years. To identify MCI status at the earliest possible point, recent studies have shown that linguistic markers such as word choice, utterance and sentence structures can potentially serve as preclinical behavioral markers. Here we present an adaptive dialogue algorithm (an AI-enabled dialogue agent) to identify sequences of questions (a dialogue policy) that distinguish MCI from normal (NL) cognitive status. Our AI agent adapts its questioning strategy based on the user's previous responses to reach an individualized conversational strategy per user. Because the AI agent is adaptive and scales favorably with additional data, our method provides a potential avenue for large-scale preclinical screening of neurocognitive decline as a new digital biomarker, as well as longitudinal tracking of aging patterns in the outpatient setting.

publication date

  • March 31, 2020

Research

keywords

  • Artificial Intelligence
  • Cognitive Dysfunction

Identity

PubMed Central ID

  • PMC7109153

Scopus Document Identifier

  • 85082791927

Digital Object Identifier (DOI)

  • 10.2196/mededu.6312

PubMed ID

  • 32235884

Additional Document Info

volume

  • 10

issue

  • 1