2024
DOI: 10.1002/cam4.7324
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Explainable machine learning predicts survival of retroperitoneal liposarcoma: A study based on theSEERdatabase and external validation in China

Maoyu Wang,
Zhizhou Li,
Shuxiong Zeng
et al.

Abstract: ObjectiveWe have developed explainable machine learning models to predict the overall survival (OS) of retroperitoneal liposarcoma (RLPS) patients. This approach aims to enhance the explainability and transparency of our modeling results.MethodsWe collected clinicopathological information of RLPS patients from The Surveillance, Epidemiology, and End Results (SEER) database and allocated them into training and validation sets with a 7:3 ratio. Simultaneously, we obtained an external validation cohort from The F… Show more

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