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Updated: May 11, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Could language deficits really differentiate Mild Cognitive Impairment (MCI) from mild Alzheimer's disease?
E Tsantali1, D Economidis, M Tsolaki
1B Internal Medicine, Geriatric Unit, Medical School, Hippocration Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece. info@tsantalieleni.gr
Abstract:
Naming abilities seem to be affected in Alzheimer's disease (AD) patients, though MCI individuals tend to exhibit greater impairments in category fluency. In this study we: (1) detect language deficits of amnestic MCIs (aMCIs) and mild AD (mAD) participants and present their language performance (the Boston Diagnostic Aphasia Examination - BDAE scores) according to educational level, (2) study the diagnostic value of language deficits according to the cognitive state of the participants. One hundred nineteen participants, 38 normal controls (NC), 28 aMCIs and 53 mADs, were recruited randomly as outpatients of 2 clinical departments and administered clinical, neuropsychological and neuroimaging assessment. Language abilities were assessed by the adapted Greek edition of the BDAE (2nd edition). Our results indicate that verbal fluency, auditory, reading comprehension and narrative ability are the main language abilities to be affected in mADs, although they are almost intact in NCs and less vulnerable in aMCIs. Narrative ability seems to be significantly impaired in mADs but not so in aMCIs. Six language subtests of the BDAE assess safely the above deficits. This brief version of the BDAE discriminated mADs from the other 2 groups 92.5% of the time, NCs 86.8% and aMCI 67.9% of the time in order to save time and to be accurate in clinical practice.
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