/Dynamic-DeepHit

Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data

Primary LanguageJupyter Notebook

Dynamic-DeepHit

Title: "Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data"

Authors: Changhee Lee, Jinsung Yoon, Mihaela van der Schaar

  • Reference: C. Lee, J. Yoon, M. van der Schaar, "Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data," IEEE Transactions on Biomedical Engineering (TBME). 2020
  • Paper: https://ieeexplore.ieee.org/document/8681104

Description of the code

This code shows the implementation of Dynamic-DeepHit on PBC2 dataset. Please see the tutorial.

Requirements

numpy==1.16.5 pandas==1.0.1 tensorflow==1.13.1 scikit-learn==0.22.1 lifelines==0.24.9  termcolor==1.1.0   scikit-survival==0.12.0