An active learning based classification strategy for the minority class problem: Application to histopathology annotation

BMC Bioinformatics

Volumn 12, Issue , 2011, Pages

  Doyle, Scott ^a   Monaco, James ^a   Feldman, Michael ^b   Tomaszewski, John ^b   Madabhushi, Anant ^a  

^a RUTGERS UNIVERSITY   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL IMAGES; CLASSIFIER PERFORMANCE; CRITICAL COMPONENT; DIGITAL PATHOLOGIES; GROUND TRUTH DATA; RECEIVER OPERATING CHARACTERISTIC CURVES; SUPERVISED CLASSIFICATION; SUPERVISED CLASSIFIERS;

COSTS; DISEASES; FORECASTING; MATHEMATICAL MODELS;

CLASSIFICATION (OF INFORMATION);

AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL INTELLIGENCE; CLASSIFICATION; GENETICS; HUMAN; MALE; PATHOLOGY; PROSTATE TUMOR; RECEIVER OPERATING CHARACTERISTIC; THEORETICAL MODEL;

AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; HUMANS; MALE; MODELS, THEORETICAL; PROSTATIC NEOPLASMS; ROC CURVE;

EID: 80055018052     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-424     Document Type: Article

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