Machine learning principles applied to CT radiomics to predict mucinous pancreatic cysts.

Adam M AweMichael M Vanden HeuvelTianyuan YuanVictoria R RendellMingren ShenAgrima KampaniShanchao LiangDane D MorganEmily R WinslowMeghan G Lubner

Published in: Abdominal radiology (New York) (2021)

Machine learning principles can be applied to PC texture features to create a mucinous phenotype classifier. Model performance did not improve with the combined model. However, specific radiomic, radiologic, and clinical features most predictive in our models can be identified using SHAP analysis.

Keyphrases

machine learning
contrast enhanced
low grade
artificial intelligence
computed tomography
big data
magnetic resonance imaging
deep learning
squamous cell carcinoma
high grade