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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Mild cognitive impairment: a systematic review.

Elena Mariani1, Roberto Monastero, Patrizia Mecocci

  • 1Section of Gerontology and Geriatrics, Department of Clinical and Experimental Medicine, University of Perugia, Perugia, Italy.

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Mild cognitive impairment (MCI) bridges normal aging and dementia. Early detection and accurate prognosis require updated criteria and multidisciplinary approaches for better patient outcomes.

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Area of Science:

  • Neurology
  • Gerontology
  • Cognitive Science

Background:

  • Mild cognitive impairment (MCI) is an intermediate state between normal aging and dementia.
  • MCI presents heterogeneous subtypes, including amnestic (aMCI) and non-amnestic (naMCI), with varying prognoses.
  • Current diagnostic and prognostic tools for MCI require enhancement.

Purpose of the Study:

  • To review recent advancements in understanding MCI.
  • To highlight the need for improved classification and prognosis of MCI.
  • To discuss markers for predicting conversion from MCI to dementia.

Main Methods:

  • Comprehensive literature review of epidemiological, clinical, neuropathological, neuroimaging, and biochemical aspects of MCI.
  • Analysis of current diagnostic criteria and their limitations.
  • Discussion of multidisciplinary diagnostic approaches.

Main Results:

  • MCI subtypes exhibit diverse etiologies and clinical presentations.
  • Heterogeneity in MCI necessitates more sensitive diagnostic instruments and reliable progression monitoring.
  • Behavioral symptoms and motor dysfunctions require better definition in MCI diagnosis and prognosis.

Conclusions:

  • Updated clinical criteria for MCI, including complex activities of daily living (ADL) restrictions, are needed.
  • A multidisciplinary approach incorporating biological and neuroimaging techniques is crucial for predicting MCI to dementia conversion.
  • Further research into MCI markers is essential for timely intervention and management.