A metodologia ROC na avaliação de um modelo fuzzy de predição do estádio patológico do tumor de próstata
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Data
2010
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Resumo
In recent years, the increase in the incidence of prostate cancer has
become a major public health problem and a challenge for medical
science. The goal of this work is assessing the performance of a
mathematical model, developed by Silveira (2007) to predict the
pathological stage of the prostate cancer, through ROC methodology
(Receiver Operating Characteristic). The model is a fuzzy rulebased
system, that combines pre-surgical data – clinical stage,
PSA level and Gleason score – availing of a set of linguistic rules
made with base on information of the existents nomograms. The
output of the system provides the possibilities of the individual,
with certain clinical features, be in each stage of the tumor
extension: localized, advanced locally and metastatic. To analyze
the discriminatory power of the fuzzy model as a diagnosis test,
was constructed from the measures of sensitivity and specificity,
the ROC curve and calculated the total area under the curve, as
measure of performance. Moreover, were obtained (in two different
ways) the cutoff points most “appropriate”, that is a threshold for
deciding between the disease is fully localized within the prostate
gland or not. Real data of patients from the Clinics Hospital of
UNICAMP were used in the calculations and the surgery – radical
prostatectomy – was used as gold standard. The results showed that
the fuzzy model in question can be used to discriminate localized
prostate cancer.
Descrição
Palavras-chave
Câncer de próstata, Diagnóstico, Conjuntos fuzzy, Curva ROC, Prostate cancer, Diagnosis, Fuzzy sets, ROC curve
Citação
SILVEIRA, Graciele Paraguaia; BARROS, Laécio Carvalho de; VENDITE, Laércio Luis; FERREIRA, Ubirajara; BILLIS, Athanase. A metodologia ROC na avaliação de um modelo fuzzy de predição do estádio patológico do tumor de próstata. Revista Brasileira de Engenharia Biomédica, Rio de Janeiro, v. 26, n. 1, p. 3-9, abril 2010.