This repository contains all of the code used to write my masters thesis on usage of deep learning methods for survival analysis. It contains 2 models, a continous-time model based on work by Katzman et al.[1] and a discrete-time model based on Lee et al.[2]

The models were evaluated on 6 survival analysis datasets, and for the MEATABRIC dataset they got evaluated on both clinical data and clinical data with mRna z scores

[1] Jared L. Katzman, Uri Shaham, Alexander Cloninger, Jonathan Bates, Tingting Jiang, and Yuval Kluger. Deepsurv: personalized treatment recommender system using a Cox proportional hazards deep neural network. BMC Medical Research Methodology, 18(1), 2018. [paper]

[2] Changhee Lee, William R Zame, Jinsung Yoon, and Mihaela van der Schaar. Deephit: A deep learning approach to survival analysis with competing risks. In Thirty-Second AAAI Conference on Artificial Intelligence, 2018. [paper]