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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 (MCI): characteristics, risk factors and prevention]

Ilan Halperin1, Amos D Korczyn

  • 1Sourasky Medical Center, Department of Neurololgy, Memory Clinic, Tel Aviv University.

Harefuah
|April 8, 2006
PubMed

Insights

Mild cognitive impairment (MCI) is a transitional stage between normal aging and dementia. Early identification and intervention in MCI are crucial for potentially preventing dementia progression.

Area of Science:

  • Neurology
  • Gerontology
  • Cognitive Science

Context:

  • Mild cognitive impairment (MCI) represents a critical phase between normal aging and dementia.
  • Despite diagnostic ambiguities, MCI signifies an elevated risk for dementia development.
  • MCI is a key target for interventions aimed at preventing dementia progression.

Purpose:

  • To summarize the current understanding and challenges in defining Mild Cognitive Impairment (MCI).
  • To highlight the significance of MCI as a precursor to dementia.
  • To underscore the importance of research into MCI's characteristics, risk factors, and prevention.

Summary:

  • Mild cognitive impairment (MCI) is characterized by cognitive function decline beyond normal aging but not yet dementia.
  • Ongoing research addresses controversies in MCI definition, frequency, and clinical presentation.
  • Significant advancements have been made in identifying neurological changes, genetic factors, and preventive strategies for MCI.

Impact:

  • Provides a comprehensive overview of Mild Cognitive Impairment (MCI) for researchers and clinicians.
  • Emphasizes the potential for therapeutic interventions during the MCI stage.
  • Contributes to a better understanding of dementia risk and prevention strategies.

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