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Figure 3 | BMC Medical Informatics and Decision Making

Figure 3

From: Stratification of coronary artery disease patients for revascularization procedure based on estimating adverse effects

Figure 3

Flowchart showing the proposed workflow. First, we split the data set into separate training and test sets. Training starts by performing binary splits according to age, sex and diabetes indication (left). The resulting 27 patient subgroups formed the leaf nodes of multiple decision trees. Each decision tree corresponds to one way of partitioning the date set (Figure 4, left). For each patient subgroup, we were seeking two classifiers: one to assess the risk of restenosis when treated with bare-metal stents (BMS; TR) and one to assess the risk of hazardous events when treated with drug-eluting stents (DES; TH). To account for varying feature availability and feature importance among subgroups and outcomes, we considered three sets of clinical features (Table 1), three sets of in vitro diagnostic biomarkers (Table 2), as well as not using any clinical and/or biomarker features. The best set of features for each patient subgroup was determined in the feature selection step. At the same time, we chose appropriate thresholds θR and θH on the predicted probabilities of restenosis (PR) and hazardous events (PH), respectively (Figure 4, right). Training was concluded by selecting the best overall classification tree by aggregating the performances of its patient subgroup-specific models. After completing training, we applied the learned classification trees TR and TH on an independent test set (right). First, we used the classification tree TR to predict P(Restenosis|BMS). If its results is negative (P R < θ R ), treatment with BMS is suggested, otherwise the second classification tree TH is used to predict P(Hazard|DES). It suggests either DES treatment, if the predicted risk of hazardous events is low (P H < θ H ), or coronary artery bypass grafting (CABG) otherwise. Finally, we evaluated the models by estimating treatment risks and costs.

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