Fig. 4. SHAP value analysis.

a Bar plots show the mean absolute SHAP value for all clinical variables used by our predictors. Purple scatter plots show individual data points. CAD history and sex are the most important clinical features for both classifiers. The central scatter plots show the impact individual feature values have on the prediction score. High feature values are depicted in a dark blue, low values in a light green. SHAP values for an existing CAD history are always positive. Similarly, SHAP values of the “sex” feature are always positive for male patients. We depict SHAP value distributions over all ages in the scatter plots on the right-hand side. b SHAP values for clinical variables and one 2-6-2 sequence of a patient. The first row shows the feature distribution of the development data set (n = 2648) in green. The blue cross marks where in the distribution the patient lies. Second row: SHAP values for the specific patient for each feature over n = 5 splits. The absence of a CAD history and the resting heart rate of 67 BPM result in negative SHAP values. The patient’s sex (male), his age, and systolic blood pressure at rest are associated with higher SHAP values. Last row: One of the patient’s 2-6-2 sequence (black) with the SHAP values of each individual measurement in the background. We show negative SHAP values in dark purple and positive ones in yellow. Dashed black lines mark the borders of pre-stress, stress, and recovery samples. The largest areas of high SHAP values concentrate in the stress phase around the ST-segment. Error bars in all plots indicate 95% confidence intervals over all models from all five splits. Box plots indicate median (middle line), 25th, and 75th percentile (box). Whiskers extend to points that lie within 1.5 IQRs of the lower and upper quartile. Diamonds are outliers. Bar plots show the mean over n = 5 test splits with error bars indicating 95% confidence intervals. Source data are provided as a Source Data file.