Development and validation of an interpretable machine learning model for predicting intraoperative HDI in PPGL based on intratumoral and peritumoral CT radiomic features

Intraoperative hemodynamic instability (HDI) might lead to severe complications for pheochromocytoma and paraganglioma (PPGL) patients. This study aims to construct a machine learning (ML) model to predict HDI based on intratumoral and peritumoral CT radiomics.

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