Screening for Early-Stage Alzheimer's Disease Using Optimized Feature Sets and Machine Learning.

Journal: Journal of Alzheimer's disease : JAD

PMID: 33780367

Abstract

BACKGROUND: Detecting early-stage Alzheimer's disease in clinical practice is difficult due to a lack of efficient and easily administered cognitive assessments that are sensitive to very mild impairment, a likely contributor to the high rate of undetected dementia.

Authors

Michael J Kleiman

Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA.
Elan Barenholtz

Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, Florida 33431, United States.
James E Galvin

Department of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, Miami, FL, United States.

Keywords

Aged Aged, 80 and over Alzheimer Disease Cognitive Dysfunction Disease Progression Female Humans Machine Learning Male Mass Screening Mental Status and Dementia Tests Middle Aged Neuropsychological Tests Sensitivity and Specificity

External Resources

View on PubMed Access via DOI PubMed (33780367)

Screening for Early-Stage Alzheimer's Disease Using Optimized Feature Sets and Machine Learning.

Abstract

Authors

Keywords

External Resources

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