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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Mild cognitive impairment

Oscar L Lopez1

  • 1lopezol@upmc.edu

Continuum (Minneapolis, Minn.)
|April 6, 2013
PubMed
Abstract

Insights

Mild cognitive impairment (MCI) describes cognitive deficits in older adults at high risk for dementia. Understanding MCI

Area of Science:

  • Neurology
  • Geriatrics
  • Cognitive Science

Background:

  • Mild cognitive impairment (MCI) signifies cognitive deficits in older adults preceding dementia.
  • MCI patients face an elevated risk of developing dementia, particularly Alzheimer's disease (AD).
  • Understanding the transition from MCI to AD is crucial for early intervention.

Purpose of the Study:

  • To review the evolving clinical concept of MCI.
  • To discuss the operationalization of current MCI definitions.
  • To explore biomarkers and treatments for MCI.

Main Methods:

  • Review of clinical criteria for MCI diagnosis.
  • Incorporation of biomarker contributions to diagnosis.
  • Assessment of challenges in bedside MCI diagnosis.

Main Results:

  • MCI is a heterogeneous syndrome, potentially coexisting with other disorders.
  • Recent criteria address diverse clinical presentations and biomarker use.
  • Accurate bedside diagnosis can be challenging due to normal cognitive scale scores.

Conclusions:

  • The article traces the clinical evolution and definitions of MCI.
  • Biomarker development aids in identifying neurodegenerative causes.
  • Proposed treatments for MCI are discussed.

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