Deep Learning Model for Predicting Rhythm Outcomes after Radiofrequency Catheter Ablation in Patients with Atrial Fibrillation

Figure 8

The Shapley additive explanation (SHAP) summary plot of the proposed model. It represents the feature importance of the model output. The color of the dots indicates the attribution value of the feature. For categorical features (CAD {0, 1}; AF type {0: paroxysmal, 1: persistent}; DM {0, 1}; HTN {0, 1}; sex {0: female, 1: male}; stroke {0, 1}; HF {0, 1}), the red and blue dots represent 1 and 0, respectively. AF, atrial fibrillation; LV, left ventricular; LVEF, left ventricular ejection fraction; LA, left atrium; eGFR, estimated glomerular filtration rate; HTN, hypertension; AF type, paroxysmal AF vs persistent AF; DM, diabetes mellitus; HF, heart failure; CAD, coronary artery disease.