Ovarian cancer classification with rejection by Bayesian Belief Networks
نویسندگان
چکیده
Belief Networks in the Bayesian approach provide a wellestablished methodology to fuse prior knowledge and statistical observations for an enriched decision support. In this paper we investigate one of the advantages of the Bayesian approach the provided additional uncertainty information for predictions in a medical classification problem. We perform a Bayesian analysis using Belief Network models to discriminate between benign and malignant ovarian masses. We report the performance of such Bayesian Belief Network models if the exclusion of some data points is allowed based on various uncertainty measures of the prediction.
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