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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

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Mild cognitive impairment: diagnosis, longitudinal course, and emerging treatments

Jennifer N Vega1, Paul A Newhouse

  • 1Center for Cognitive Medicine, Department of Psychiatry, Vanderbilt University School of Medicine, 1601 23rd Ave. S., Nashville, TN, 37212, USA.

Current Psychiatry Reports
|August 28, 2014
PubMed

Insights

Mild cognitive impairment (MCI) is a critical stage between normal aging and dementia, particularly Alzheimer's disease (AD). Research is evolving to better diagnose and treat MCI, though effective therapies remain elusive.

Area of Science:

  • Neurology
  • Gerontology
  • Cognitive Science

Background:

  • Mild cognitive impairment (MCI) signifies a stage between normal aging and dementia.
  • Elderly individuals with MCI face a heightened risk of developing dementia, especially Alzheimer's disease (AD).

Purpose of the Study:

  • To provide an overview of the evolving concept and diagnostic criteria for MCI.
  • To review the longitudinal progression of MCI.
  • To summarize current and emerging therapeutic strategies for MCI.

Main Methods:

  • Review of the evolution of MCI diagnostic criteria.
  • Analysis of the longitudinal course and prognostic implications of MCI.
  • Survey of existing and investigational treatments for MCI.

Main Results:

  • The definition and diagnosis of MCI continue to evolve.
  • Prognostic indicators for cognitive decline in MCI are becoming clearer.
  • Clinical trials for MCI interventions have yielded mixed results, with no definitive treatment established.

Conclusions:

  • MCI represents a crucial target for early intervention in cognitive decline.
  • Further research is needed to develop effective treatments for MCI to prevent progression to dementia.

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