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A tree augmented naive Bayesian network experiment for breast cancer prediction

In order to investigate the breast cancer prediction problem on the aging population with the grades of DCIS, we conduct a tree augmented naive Bayesian network experiment trained and tested on a large clinical dataset including consecutive diagnostic mammography examinations, consequent biopsy outcomes and related cancer registry records in the population of women across all ages. The aggregated results of our ten-fold cross validation method recommend a biopsy threshold higher than 2% for the aging population.

preprint2015arXivOpen access
Ping Ren
Machine LearningQuantitative Methods
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Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
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Ping Ren

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