A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets

Pritam Mukherjee, Mu Zhou, Edward Lee, Anne Schicht, Yoganand Balagurunathan, Sandy Napel, Robert J. Gillies, Simon Wong, Alexander Thieme, Ann N. Leung, Olivier Gevaert

Abstract: Predicting overall survival for patients with confirmed non-small-cell lung cancer is an important issue in clinical practice. The authors developed and validated in four independent patient cohorts a shallow convolutional neural network that can predict the outcomes of individuals using pre-treatment CT images. The authors further show that the survival model can be used, via transfer learning, for classifying benign versus malignant nodules.