MUSC-TBIC/etude-engine
ETUDE (Evaluation Tool for Unstructured Data and Extractions) is a Python-based tool that provides consistent evaluation options across a range of annotation schemata and corpus formats
This tool helps researchers and clinical informaticists evaluate the accuracy of systems that automatically extract information from unstructured text, such as medical notes. You input a collection of documents with "gold standard" human annotations and another collection with machine-generated annotations. The tool then outputs detailed performance metrics like true positives, false positives, and false negatives, allowing you to assess how well your automated system performs at identifying specific types of information.
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Use this if you need to rigorously compare the quality of information extracted by an automated system against human-annotated ground truth data in text documents.
Not ideal if you are looking for a tool to perform the actual annotation of text or if your primary goal is to train a new information extraction model rather than evaluate an existing one.
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Jupyter Notebook
License
Apache-2.0
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Last pushed
Jul 22, 2022
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