A new neural network model extends word embedding vectors with MeSH concepts for biomedical semantic similarity.
problem Eliciting semantic similarity between biomedical concepts remains challenging.
method Proposes a MeSH-gram neural network model that extends skip-gram by using MeSH descriptors.
result MeSH-gram outperforms skip-gram and is comparable to best methods but requires more computation and external resources.