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Survival prediction and treatment recommendation with Bayesian techniques in lung cancer.

Abstract:

In this paper, we investigate a number of Bayesian techniques for predicting 1-year- survival and making treatment selection recommendations for lung cancer. We have carried out two sets of experiments on the English Lung Cancer Dataset. For 1-year-survival prediction, the Naïve Bayes (NB) algorithm achieved an area under the curve value of 81%, outperforming the Bayesian Networks learned by the M(3) and K2 structure learning algorithms. For treatment recommendation, the Bayesian Network, who...

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Authors


Alcantara, RB More by this author
Journal:
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Volume:
2012
Pages:
838-847
Publication date:
2012
EISSN:
1942-597X
URN:
uuid:f8e646d4-5ab1-4772-b811-adbd5a01648a
Source identifiers:
387118
Local pid:
pubs:387118

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