Implemetation of Gibbs sampling algorithm for learning a Latent Dirichlet Allocation topic model on EHR (ICD-codes) data.
To run the code, clone repository, and run, python lda_gibbs_sampling.py .
You'll need to install the following packages:
- pandas - for loading the data
- numpy - for efficient computations
- seaborn - for visualizations
- matplotlib - for visualizations
The implementation is based on the following article.
Darling, William M. "A theoretical and practical implementation tutorial on topic modeling and gibbs sampling." Proceedings of the 49th annual meeting of the association for computational linguistics: Human language technologies. 2011.
The data used for this example can be obtained from: https://mimic.physionet.org/
MIMIC-III, a freely accessible critical care database. Johnson AEW, Pollard TJ, Shen L, Lehman L, Feng M, Ghassemi M, Moody B, Szolovits P, Celi LA, and Mark RG. Scientific Data (2016). DOI: 10.1038/sdata.2016.35. Available at: http://www.nature.com/articles/sdata201635
