This repo contains the code associated with the following paper (under review):
Beam, A.L., Kompa, B., Schmaltz, A., Fried, I., Griffin, W, Palmer, N.P., Shi, X., Cai, T., and Kohane, I.S.,, 2019. Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data. arXiv preprint arXiv:1804.01486.
Supplementary Material for this paper is available here: https://www.dropbox.com/s/lesmmry083ymloo/supplemental_figures.pdf?dl=0
This repo contains the R pacakge cui2vec, which provides code for fitting embeddings to your own co-occurrence data in the manner presented in the above paper. The package can be installed locally from source. An overview of usage is provided in the following HTML vignette, which can be viewed in your browser:
vignettes/rendered/2019_07_31/cui2vecWorkflow.html.
Additional information on each of the public functions can be accessed in the standard way (e.g., ?cui2vec::construct_word2vec_embedding).
Data agreements prevent us from releasing all of our original source data, but the embeddings are available at the following URL: https://figshare.com/s/00d69861786cd0156d81
You can access an interactive explorer here: http://cui2vec.dbmi.hms.harvard.edu/