Results of the computational predictions of patient diagnosis on the complete dataset.

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. 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 imbalance: 29.63% positive data instances (all the 96 mesothelioma patients), and 70.37% negative data instances (all the 228 non-mesothelioma patients).马修斯相关系数（Matthews correlation coefficient, MCC）：对应公式3。准确率：对应公式1。F1分数（F1 score）：对应公式4。灵敏度（Sensitivity，真阳性率）：对应公式5。特异度（Specificity，真阴性率）：对应公式6。所有指标值均为程序独立运行十次所得结果的中位数。本研究同时报告了各方法在数据集全部特征上的应用结果，以及仅使用两项选定特征的决策树模型结果，即标题为「决策树（仅应用于肺侧与血小板计数）」的行。数据集类别不平衡情况为：阳性数据实例占比29.63%（全部96例间皮瘤患者），阴性数据实例占比70.37%（全部228例非间皮瘤患者）。