Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status


Kocak B., Durmaz E. S. , Ates E., Ulusan M. B.

AMERICAN JOURNAL OF ROENTGENOLOGY, cilt.212, 2019 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 212 Konu: 3
  • Basım Tarihi: 2019
  • Doi Numarası: 10.2214/ajr.18.20443
  • Dergi Adı: AMERICAN JOURNAL OF ROENTGENOLOGY

Özet

OBJECTIVE. The purpose of this study is to evaluate the potential value of machine learning (ML)-based high-dimensional quantitative CT texture analysis in predicting the mutation status of the gene encoding the protein polybromo-1 (PBRM1) in patients with clear cell renal cell carcinoma (RCC).