Spectral Embedding Based Probabilistic boosting Tree (ScEPTre): Classifying high dimensional heterogeneous biomedical data

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

Volumn 5762 LNCS, Issue PART 2, 2009, Pages 844-851

  Tiwari, Pallavi ^a   Rosen, Mark ^b   Reed, Galen ^c   Kurhanewicz, John ^c   Madabhushi, Anant ^a  

^a RUTGERS UNIVERSITY   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL DATA; CLASSIFICATION RESULTS; CLASSIFICATION SCHEME; CROSS VALIDATION; CURSE OF DIMENSIONALITY; DATA CLASS; DATA CLASSIFICATION; DATA INTEGRATION; DATA REPRESENTATIONS; DIMENSIONAL SPACES; FEATURE REPRESENTATION; HAAR WAVELETS; HIGH DIMENSIONAL DATA; HIGH-DIMENSIONAL; INDIVIDUAL CLASSIFIERS; LOW DIMENSIONAL EMBEDDING; MRI AND MRS; PROSTATE CANCER DETECTION; RECEIVER OPERATING CURVES; TREE CLASSIFIERS;

CLASSIFIERS; CLUSTERING ALGORITHMS; FACE RECOGNITION; MEDICAL COMPUTING; RESONANCE;

TREES (MATHEMATICS);

TUMOR MARKER;

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; HUMAN; MALE; METABOLISM; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PROSTATE TUMOR; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS;

ALGORITHMS; DATA INTERPRETATION, STATISTICAL; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; MAGNETIC RESONANCE IMAGING; MAGNETIC RESONANCE SPECTROSCOPY; MALE; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TUMOR MARKERS, BIOLOGICAL;

EID: 84857990337     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_102     Document Type: Conference Paper

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