Usefulness of Random Forest Algorithm in Predicting Severe Acute Pancreatitis

Wandong Hong, Yajing Lu, Xiaoying Zhou, Shengchun Jin, Jingyi Pan, Qingyi Lin, Shaopeng Yang, Zarrin Basharat, Maddalena Zippi, Hemant Goyal

Frontiers in Cellular and Infection Microbiology · 2022 · 38 citations · 72 references

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Abstract

An interpretable RF model exhibited the highest discriminatory performance in predicting SAP. Interpretation with LIME plots could be useful for individualized prediction in a clinical setting. A nomogram consisting of albumin, serum creatinine, glucose, and pleural effusion was useful for prediction of SAP.

References

72