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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Mild cognitive impairment: a concept in evolution
R C Petersen1, B Caracciolo, C Brayne
1From the Mayo Alzheimer's Disease Research Center, Mayo Clinic College of Medicine, Rochester, MN, USA.
Abstract:
The construct of mild cognitive impairment (MCI) has evolved over the past 10 years since the publication of the new MCI definition at the Key Symposium in 2003, but the core criteria have remained unchanged. The construct has been extensively used worldwide, both in clinical and in research settings, to define the grey area between intact cognitive functioning and clinical dementia. A rich set of data regarding occurrence, risk factors and progression of MCI has been generated. Discrepancies between studies can be mostly explained by differences in the operationalization of the criteria, differences in the setting where the criteria have been applied, selection of subjects and length of follow-up in longitudinal studies. Major controversial issues that remain to be further explored are algorithmic versus clinical classification, reliability of clinical judgment, temporal changes in cognitive performances and predictivity of putative biomarkers. Some suggestions to further develop the MCI construct include the tailoring of the clinical criteria to specific populations and to specific contexts. The addition of biomarkers to the clinical phenotypes is promising but requires deeper investigation. Translation of findings from the specialty clinic to the population setting, although challenging, will enhance uniformity of outcomes. More longitudinal population-based studies on cognitive ageing and MCI need to be performed to clarify all these issues.
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