NILE

Narrative Information Linear Extraction

Introduction

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.

Download

NILE is currently provided in two forms:

  • Java Package
    The Java package is intended for data scientist who are familiar with Java programming, operated via simple APIs for maximum flexibility. The package includes user manual and a working example.
    Download (java)

  • Windows Executable
    The Windows executable provides simplified operations by using a configuration file access, incorporating additional features such as multi-threading and database access that can be operated by people without programming background.
    Download (.exe) View User Guide

Example

Click here to view an example of generating NLP features using NILE.

Reference

Yu S, Cai T, Cai T. NILE: Fast Natural Language Processing for Electronic Health Records. doi: 10.48550/arXiv.1311.6063.