A new cluster-based oversampling method for improving survival prediction of hepatocellular carcinoma patients

Journal of Biomedical Informatics

Volumn 58, Issue , 2015, Pages 49-59

  Santos, Miriam Seoane ^a,b   Abreu, Pedro Henriques ^a,b   García Laencina, Pedro J ^c   Simão, Adélia ^d   Carvalho, Armando ^d  

^a UNIVERSITY OF COIMBRA   (Portugal)

^b UNIVERSITY OF COIMBRA   (Portugal)

^c Centro Universitario de la Defensa de San Javier   (Spain)

^d CENTRO HOSPITALAR E UNIVERSITÁRIO DE COIMBRA   (Portugal)

Author keywords

Clustering; Hepatocellular Carcinoma (HCC); K means; Oversampling; SMOTE; Survival prediction

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLUSTERING ALGORITHMS; COMPLEX NETWORKS; DATA MINING; DECISION MAKING; DISEASES; FORECASTING; LEARNING SYSTEMS;

CLUSTERING; HEPATOCELLULAR CARCINOMA; K-MEANS; OVER SAMPLING; SMOTE; SURVIVAL PREDICTION;

PATIENT TREATMENT;

ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER SURVIVAL; CLASSIFICATION ALGORITHM; CLUSTER ANALYSIS; CLUSTER BASED OVERSAMPLING METHOD; CONTROLLED STUDY; FRIEDMAN TEST; HUMAN; INTERMETHOD COMPARISON; KERNEL METHOD; LIVER CELL CARCINOMA; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MATHEMATICAL COMPUTING; MEASUREMENT ACCURACY; METHODOLOGY; PRIORITY JOURNAL; SURVIVAL PREDICTION; SURVIVAL TIME; LIVER TUMOR; PATHOPHYSIOLOGY;

CARCINOMA, HEPATOCELLULAR; CLUSTER ANALYSIS; HUMANS; LIVER NEOPLASMS;

EID: 84947934366     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2015.09.012     Document Type: Article

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