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Updated: Aug 15, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Brief assessment of severe language impairments: initial validation of the Mississippi aphasia screening test
R Nakase-Thompson1, E Manning, M Sherer
1Department of Neuropsychology, Methodist Rehabilitation Center, Jackson, MI 39216, USA. nakase@aol.com
Primary Objective:
To validate the Mississippi Aphasia Screening Test (MAST) which includes nine sub-scales measuring expressive and receptive language abilities.
Research Design:
Evaluation of inpatients admitted to neurology, neurosurgery or rehabilitation units at two local hospitals and who were within 60 days of onset of a unilateral ischemic or haemorrhagic stroke (left hemisphere (LH; n=38); right hemisphere (RH; n=20)). Additional participants were recruited from the community to comprise a non-patient control sample (NP; n=36).
Methods:
Data collection included administration of the MAST and chart review.
Results:
The LH group showed more impairment than the RH and NP groups on summary scores. The LH group performed worse than the NP group on all sub-scales. The object recognition and verbal fluency sub-scales did not discriminate the stroke groups.
Conclusion:
Analyses suggest good criterion validity for the MAST in differentiating communication impairments among clinical and control samples.

