benchmark_comorbidities: Benchmarking comorbidities task
In beamandrew/cui2vec: cui2vec Word Embeddings for Multimodal Data

The benchmarking strategy leverages previously published ‘known’ relationships between medicalconcepts. We compare how similar the embeddings for a pair of concepts are by computing the cosine similarity of their corresponding vectors, and use this similarity to assess whether or not thetwo concepts are related. benchmark_comorbidities focuses on an embedding's ability to identify comorbidities. A comorbidity is a disease or condition that frequently accompanies a primary diagnosis.

1 2	benchmark_comorbidities(embedding_df, sig_level = 0.05, bootstraps = 10000)

`embedding_df`	The embedding dataframe with bound semantic types
`sig_level`	The significance level threshold
`bootstraps`	The number of bootstraps to perform