Nonlinear discriminant analysis and prognostic factor classification in node-negative primary breast cancer using probabilistic neural networks

Anticancer Research

Volumn 20, Issue 3 B, 2000, Pages 2213-2218

  Le Goff, J M ^a   Lavayssiere L ^a   Rouesse J ^b   Spyratos, F ^b  

^a AVENTI Co   (France)

^b CENTRE RENÉ HUGUENIN   (France)

Author keywords

Discriminant analysis; Kernel; Neural networks; Primary breast cancer; Probability; Prognosis

Indexed keywords

EPIDERMAL GROWTH FACTOR RECEPTOR; ESTROGEN RECEPTOR; ONCOPROTEIN; PROGESTERONE RECEPTOR; PROTEIN P53; UROKINASE;

ADULT; AGE; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST CANCER; CANCER GRADING; CANCER RECURRENCE; DATA BASE; DISCRIMINANT ANALYSIS; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MENOPAUSE; PRIORITY JOURNAL; PROBABILITY; PROGNOSIS; TUMOR VOLUME;

AGE FACTORS; ALGORITHMS; BAYES THEOREM; BREAST NEOPLASMS; DATABASES, FACTUAL; DISCRIMINANT ANALYSIS; ESTROGENS; FEMALE; HUMANS; MENOPAUSE; NEOPLASM PROTEINS; NEOPLASM RECURRENCE, LOCAL; NEOPLASMS, HORMONE-DEPENDENT; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; PROGESTERONE; PROGNOSIS; RECEPTOR, EPIDERMAL GROWTH FACTOR; RECEPTOR, ERBB-2; RECEPTORS, ESTROGEN; RECEPTORS, PROGESTERONE; RISK FACTORS; ROC CURVE; TREATMENT OUTCOME; TUMOR MARKERS, BIOLOGICAL; TUMOR SUPPRESSOR PROTEIN P53; URINARY PLASMINOGEN ACTIVATOR;

EID: 0033869134     PISSN: 02507005     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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