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Updated: Feb 1, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Identifying Cognitive Impairment in an Older Adult Using Two Different Screening Tools
Abstract:
A 78-year-old Hispanic woman presented to an ambulatory care clinic for older adults describing memory impairment and requesting an assessment of her cognitive status. A Mini-Mental State Examination (MMSE) was performed and found to be 29/30 (normal). One year later, the same situation occurred and her MMSE was again found to be 29/30 (normal). However, a Saint Louis University Mental Status (SLUMS) examination administered that same day demonstrated a different result: a score of 19/30 (dementia). Fourteen months later, the patient returned again and scored 26/30 (normal) on the MMSE and 22/30 (mild neurocognitive disorder) on the SLUMS. Our patient case illustrates inherent differences between the MMSE and SLUMS in the ability to detect mild cognitive impairment and dementia, along with the variability that may occur with testing.
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