Prediction of 5-year progression-free survival in advanced nasopharyngeal carcinoma with pretreatment PET/CT using multi-modality deep learning-based radiomics

  title={Prediction of 5-year progression-free survival in advanced nasopharyngeal carcinoma with pretreatment PET/CT using multi-modality deep learning-based radiomics},
  author={Bingxin Gu and Mingyuan Meng and Lei Bi and Jinman Kim and David Dagan Feng and Shaoli Song},
  journal={Frontiers in Oncology},
Objective Deep learning-based radiomics (DLR) has achieved great success in medical image analysis and has been considered a replacement for conventional radiomics that relies on handcrafted features. In this study, we aimed to explore the capability of DLR for the prediction of 5-year progression-free survival (PFS) in advanced nasopharyngeal carcinoma (NPC) using pretreatment PET/CT images. Methods A total of 257 patients (170/87 patients in internal/external cohorts) with advanced NPC (TNM… 

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