The application of unsupervised clustering methods to Alzheimer’s disease

Frontiers in Computational Neuroscience

Volumn 13, Issue , 2019, Pages

  Alashwal, Hany ^a   El Halaby, Mohamed ^b   Crouse, Jacob J ^c   Abdalla, Areeg ^b   Moustafa, Ahmed A ^d  

^a UNITED ARAB EMIRATES UNIVERSITY   (United Arab Emirates)

^b CAIRO UNIVERSITY   (Egypt)

^c UNIVERSITY OF SYDNEY   (Australia)

^d UNIVERSITY OF WESTERN SYDNEY   (Australia)

Author keywords

Alzheimer s disease; Clustering; Machine learning techniques; Neurological diseases; Unsupervised learning

Indexed keywords

CLUSTER ANALYSIS; MACHINE LEARNING; NEUROLOGY; UNSUPERVISED LEARNING;

ALZHEIMER; CLUSTERING; CLUSTERING ANALYSIS; CLUSTERING TECHNIQUES; MACHINE LEARNING TECHNIQUES; MEDICAL PRACTITIONER; NEUROLOGICAL DISEASE; UNSUPERVISED CLUSTERING METHODS;

CLUSTERING ALGORITHMS;

ALZHEIMER DISEASE; CEREBROSPINAL FLUID ANALYSIS; DISEASE COURSE; FOLLOW UP; HUMAN; LEARNING ALGORITHM; MACHINE LEARNING; MEDICAL HISTORY; MILD COGNITIVE IMPAIRMENT; MINI MENTAL STATE EXAMINATION; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSICIAN; POPULATION RESEARCH; REVIEW; SEX DIFFERENCE; UNSUPERVISED LEARNING;

EID: 85068487040     PISSN: None     EISSN: 16625188     Source Type: Journal    
DOI: 10.3389/fncom.2019.00031     Document Type: Review

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