Multi-stage biomarker models for progression estimation in Alzheimer’s disease

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9123, Issue , 2015, Pages 387-398

  Schmidt Richberg, Alexander ^a   Guerrero, Ricardo ^a   Ledig, Christian ^a   Molina Abril, Helena ^b   Frangi, Alejandro F ^b   Rueckert, Daniel ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

NEUROIMAGING;

CLASSIFICATION TASKS; DISEASE PROGRESSION; LONGITUDINAL STUDY; MILD COGNITIVE IMPAIRMENTS (MCI); MULTI STAGE; OBSERVATION WINDOW; PROBABILISTIC APPROACHES; QUANTILE REGRESSION;

BIOMARKERS;

BIOLOGICAL MARKER;

ALGORITHM; ALZHEIMER DISEASE; ANATOMIC LANDMARK; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPLICATION; COMPUTER ASSISTED DIAGNOSIS; DISEASE COURSE; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ALZHEIMER DISEASE; ANATOMIC LANDMARKS; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MARKERS; DISEASE PROGRESSION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MILD COGNITIVE IMPAIRMENT; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84983528529     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-19992-4_30     Document Type: Conference Paper

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