Machine Learning classification of MRI features of Alzheimer's disease and mild cognitive impairment subjects to reduce the sample size in clinical trials

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2011, Pages 7957-7960

  Escudero, Javier ^a   Zajicek, John P ^b   Ifeachor, Emmanuel ^a  

^a UNIVERSITY OF PLYMOUTH   (United Kingdom)

^b PLYMOUTH UNIVERSITY PENINSULA SCHOOLS OF MEDICINE AND DENTISTRY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY RATE; ALZHEIMER'S DISEASE; CLINICAL TRIAL; COGNITIVE IMPAIRMENT; CONTROL SUBJECT; GROUP SIZE; MACHINE LEARNING CLASSIFICATION; SAMPLE SIZES;

EXPERIMENTS; LEARNING SYSTEMS; MAGNETIC RESONANCE IMAGING; NEURODEGENERATIVE DISEASES;

CLASSIFICATION (OF INFORMATION);

AGED; ALZHEIMER DISEASE; ARTICLE; ARTIFICIAL INTELLIGENCE; CLASSIFICATION; CLINICAL TRIAL (TOPIC); DEMOGRAPHY; FEMALE; HUMAN; MALE; METHODOLOGY; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; SAMPLE SIZE;

AGED; ALZHEIMER DISEASE; ARTIFICIAL INTELLIGENCE; CLINICAL TRIALS AS TOPIC; DEMOGRAPHY; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MILD COGNITIVE IMPAIRMENT; SAMPLE SIZE;

EID: 84861658596     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2011.6091962     Document Type: Conference Paper

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