https://www.selleckchem.com/products/r428.html
There is an increasing number of patients with a first primary cancer who are diagnosed with a second primary cancer, but prognosis methods to predict the survivability of a patient with multiple primary cancers have not been fully benchmarked. This study investigated the five-year survivability prognosis performances of six machine learning approaches. These approaches are artificial neural network, decision tree (DT), logistic regression, support vector machine, naïve Bayes (N, and Bayesian network (BN). A synthetic minority over-sampl
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