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Fig. 5 | BMC Medical Informatics and Decision Making

Fig. 5

From: Interpretable machine-learning model for Predicting the Convalescent COVID-19 patients with pulmonary diffusing capacity impairment

Fig. 5

Top 6 clinical features in SHAP values of XGBoost. A Hb, B MVV, C severity of illness, D PLT, E UA, F BUN. Values are plotted with a scatter plot. The morbidity of PDCI predicted by the model will be increased when the SHAP value of the feature is > 0, and the disease-free rate of PDCI predicted by the model will be increased when the SHAP value is < 0. MVV: maximal voluntary ventilation; HB: hemoglobin, PLT: platelets; BUN: blood urea nitrogen; UA: uric acid

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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