You are viewing the site in preview mode

Skip to main content
Fig. 4 | BMC Medical Informatics and Decision Making

Fig. 4

From: Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy

Fig. 4

The SHAP summary plots for the 13 clinical features affecting the XGBoost model. A Feature importance ranking according to SHAP in the training set. B Feature importance ranking according to SHAP in the validation set. C Summary plot of SHAP values in the training set. D Summary plot of SHAP values in the validation set. From top to bottom, the influence of features on the model gradually decreases. If the horizontal sample distribution is relatively scattered, it means that the feature has a greater impact. Yellow dots represent higher observation values, while purple dots represent lower observation values

Back to article page

BMC Medical Informatics and Decision Making

ISSN: 1472-6947

Contact us