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Updated: Mar 9, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Alzheimer's disease patient groups derived from a multivariate analysis of cognitive test outcomes in the Coalition
Inna Tishchenko1, Carlos Riveros2, Pablo Moscato1
1Information-Based Medicine Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia; School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, NSW, Australia; Information-Based Medicine Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia; School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, NSW, Australia.
Aim:
The mini-mental state examination, commonly used to measure cognitive impairment of Alzheimer's disease (AD) patients, consists of five test categories. The final score is calculated as their total sum, implying a loss of information.
Materials & Methods:
In this study, we propose a new multivariate approach to address this issue.
Results:
We analyzed the current largest AD-related coalition against major diseases dataset comprising 3717 patients of interest. Our clustering approach revealed five groups of patients associated with distinct characteristics and prognosis. Interestingly, only three cognitive test categories significantly contribute to their determination: registration, attention and recall.
Conclusion:
The insight that only these categories are critical for AD group determination may help to resolve the patients' educational background issue often discussed in relation to the mini-mental state examination assessment.
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