NILE is an efficient and effective software for natural language processing (NLP) of clinical narrative texts. It uses a prefix tree algorithm for named entity recognition, and finite-state machines for semantic analysis, both of which were inspired by the natural reading behavior of humans. The design aims to directly translate linguistic and clinical knowledge to code, allowing for the development of functions to parse complex language patterns.
The software was developed by Sheng Yu and Tianxi Cai at Harvard T.H. Chan School of Public Health and Tianrun Cai at The Brigham and Women’s Hospital. It is distributed free of charge for academic and non-commercial research use by the President and Fellows of Harvard College.
