Variable importance in nonlinear kernels (VINK): Classification of digitized histopathology

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

Volumn 8150 LNCS, Issue PART 2, 2013, Pages 238-245

  Ginsburg, Shoshana ^a   Ali, Sahirzeeshan ^a   Lee, George ^b   Basavanhally, Ajay ^b   Madabhushi, Anant ^a  

^a Case Western Reserve University   (United States)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CURSE OF DIMENSIONALITY; DIMENSIONALITY REDUCTION; EIGENVECTORS AND EIGENVALUES; HIGH DIMENSIONAL FEATURE; HIGH-DIMENSIONAL FEATURES; IMAGE-BASED FEATURES; PRINCIPAL COMPONENTS ANALYSIS; RADICAL PROSTATECTOMY;

CLASSIFICATION (OF INFORMATION); EIGENVALUES AND EIGENFUNCTIONS;

PRINCIPAL COMPONENT ANALYSIS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOPSY; COMPUTER ASSISTED DIAGNOSIS; FEMALE; HUMAN; IMAGE ENHANCEMENT; MALE; METHODOLOGY; MICROSCOPY; NONLINEAR SYSTEM; PATHOLOGY; PROSTATE TUMOR; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOPSY; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MALE; MICROSCOPY; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84897571026     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40763-5_30     Document Type: Conference Paper

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