Region-of-Interest based sparse feature learning method for Alzheimer's disease identification
Comput. Methods Programs Biomed., pp. 1052902019.
Alzheimer’s diseaseComputer-aided disease diagnosisElastic netMachine learningSparse feature learning
The extracted features and the proposed identification parameters show high correlation with the volume of GM and the clinical mini-mental state examination (MMSE) score respectively. The proposed method will be useful in denoting the changes of cerebral pathology and cognitive function in AD patients.
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