Results of the computational predictions of patient diagnosis, after under-sampling.

Matthews correlation coefficient (MCC): Eq 3. Accuracy: Eq 1. F1 score: Eq 4. Sensitivity (true positive rate): Eq 5. Specificity (true negative rate): Eq 6. The scores are the medians of the results’ ten separate program executions, run with different subset content selected randomly for training set, validation set, and test set every time. We report the results of the application of the methods on all the dataset features, plus the results of the decision tree only to the two selected features: the row entitled “Decision tree (applied only to lung side & platelet count)”. Dataset balance: 50% positive data instances (all the 96 mesothelioma patients), and 50% negative data instances (96 non-mesothelioma patients, randomly selected). Perceptron: learning rate = 0.1.