Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study.
Ahmed HosnyChintan ParmarThibaud P CorollerPatrick GrossmannRoman ZeleznikAvnish KumarJohan BussinkRobert James GilliesRaymond H MakHugo J W L AertsPublished in: PLoS medicine (2018)
Our results provide evidence that deep learning networks may be used for mortality risk stratification based on standard-of-care CT images from NSCLC patients. This evidence motivates future research into better deciphering the clinical and biological basis of deep learning networks as well as validation in prospective data.
Keyphrases
- current status
- deep learning
- convolutional neural network
- artificial intelligence
- machine learning
- end stage renal disease
- healthcare
- small cell lung cancer
- ejection fraction
- newly diagnosed
- contrast enhanced
- big data
- computed tomography
- magnetic resonance imaging
- prognostic factors
- peritoneal dialysis
- risk factors
- cardiovascular disease
- advanced non small cell lung cancer
- pain management
- dual energy
- image quality
- tyrosine kinase
- patient reported