clinspacy

Performs biomedical named entity recognition, Unified Medical Language System (UMLS) concept mapping, and negation detection using the Python 'spaCy', 'scispaCy', and 'medspaCy' packages, and transforms extracted data into a wide format for inclusion in machine learning models. The development of the 'scispaCy' package is described by Neumann (2019) doi:10.18653/v1/W19-5034. The 'medspacy' package uses 'ConText', an algorithm for determining the context of clinical statements described by Harkema (2009) doi:10.1016/j.jbi.2009.05.002. Clinspacy also supports entity embeddings from 'scispaCy' and UMLS 'cui2vec' concept embeddings developed by Beam (2018) .