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Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer.

Paul Blanc-DurandLuca CampedelSébastien MuleSimon JegouAlain LucianiFrédéric PigneurEmmanuel Itti
Published in: European radiology (2020)
• Deep learning will make CT-derived anthropometric measures clinically usable as they are currently too time-consuming to calculate in routine practice. • Whole-body CT-derived anthropometrics in non-small-cell lung cancer are associated with progression-free survival and overall survival. • A priori medical knowledge can be implemented in the neural network loss function calculation.
Keyphrases
  • deep learning
  • free survival
  • image quality
  • dual energy
  • neural network
  • healthcare
  • computed tomography
  • contrast enhanced
  • body composition
  • positron emission tomography
  • primary care
  • artificial intelligence