Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus

Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus

Abstract This study sought to establish and validate an interpretable CT radiomics-based machine learning model capable of predicting post-acute pancreatitis diabetes mellitus (PPDM-A), providing clinicians with an effective predictive tool to aid patient management in a timely fashion. Clinical and...

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Bibliographic Details
Main Authors: Xiyao Wan, Yuan Wang, Ziyi Liu, Ziyan Liu, Shuting Zhong, Xiaohua Huang
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Acute pancreatitis
Diabetes
CT scan
Radiomics
Interpretability
Online Access:https://doi.org/10.1038/s41598-025-86290-7
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https://doi.org/10.1038/s41598-025-86290-7

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