Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach

Table 6 The sensitivity, specificity, and positive likelihood ratio of predicting the index MDT decisions using the best machine learning model versus using ESMO and NCCN guidelines

The sensitivity (sens), specificity (spec), and the positive likelihood ratio (LR+) when using the best machine learning models or guideline to predict MDT recommendations
Note: ^aThe best models were ripple down rules for the chemotherapy decisions, polynomial SVM for the aggressive endocrine decisions, and ADTree for the remaining groups
^bpairwise comparisons of likelihood ratios using two-sided z-test (i.ebest model vs. guideline)
^cthe best model performed better than the guideline

ISSN: 1471-2407