Login / Signup

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