Jul 25, 2020

[Formula: see text]: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer

Scientific reports
Parnian Afshar, Arash Mohammadi, Pascal N Tyrrell, Patrick Cheung, Ahmed Sigiuk, Konstantinos N Plataniotis, Elsie T Nguyen, Anastasia Oikonomou
Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account. Furthermore, accurate segmentation of the tumor is required for development of a reliable predictive model, which may be objective and a time-consuming task. To address these drawbacks, we propose a deep learning-based radiomics model for the...