The TEBM is a generative model that can estimate the timing and uncertainty of events from semi-longitudinal datasets with irregularly sampled and missing data.
If you use the TEBM, please cite this paper:
Wijeratne, P.A., Eshaghi, A., Scotton, W.J., et al. The temporal event-based model: learning event timelines in progressive diseases. Imaging Neuroscience 2023. doi: https://doi.org/10.1162/imag_a_00010
Linux OS (Ubuntu 16.04.1, or greater)
g++>=7.5.0
c++>=3.8.0
python>=3.7
numpy>=1.19.5
scipy>=1.7.3
pandas
pickle
pathos
matplotlib
Install and link "kde_ebm" package, available here:
https://github.com/ucl-pond/kde_ebm
Navigate to top directory and issue the following command:
CC=g++ CFLAGS=-lstdc++ python setup.py install
Navigate to examples/ and issue the following command:
python run_tebm_sim.py
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