Risk group detection and survival function estimation for interval coded survival methods

Neurocomputing

Volumn 112, Issue , 2013, Pages 200-210

  Van Belle, Vanya ^a,b   Neven, Patrick ^c   Harvey, Vernon ^d   Van Huffel, Sabine ^a   Suykens, Johan A K ^a   Boyd, Stephen ^e  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b LIVERPOOL JOHN MOORES UNIVERSITY   (United Kingdom)

^c UNIVERSITY HOSPITALS LEUVEN   (Belgium)

^d AUCKLAND CITY HOSPITAL   (New Zealand)

^e Stanford University   (United States)

Author keywords

Breast cancer prognosis; Monotonic regression; Survival analysis

Indexed keywords

ADVANCED MODELING TECHNIQUES; BREAST CANCER PROGNOSIS; INTERPRETABILITY; MONOTONIC REGRESSIONS; PROPORTIONAL HAZARD MODELS; SURVIVAL ANALYSIS; SURVIVAL CURVES; SURVIVAL FUNCTION;

BRIDGES; CURVE FITTING; DESIGN; INTELLIGENT CONTROL;

RISK PERCEPTION;

EPIDERMAL GROWTH FACTOR RECEPTOR; PROGESTERONE;

ARTICLE; BREAST CANCER; CANCER GRADING; CANCER PROGNOSIS; CLUSTER ANALYSIS; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; HIGH RISK POPULATION; HUMAN; INTERMETHOD COMPARISON; INTERVAL CODED SCORE METHOD; KAPLAN MEIER METHOD; MAJOR CLINICAL STUDY; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROPORTIONAL HAZARDS MODEL; PROTEIN EXPRESSION; RISK ASSESSMENT; SCORING SYSTEM; STATISTICAL ANALYSIS; SUPPORT VECTOR MACHINE; SURVIVAL PREDICTION; SURVIVAL RATE; SURVIVAL TIME; VALIDATION STUDY;

EID: 84877589964     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.12.049     Document Type: Article

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