allenyummy/EHR_NER
Nested Named Entity Recognition for Chinese Electronic Health Records with QA-based Sequence Labeling
This project helps medical professionals, researchers, or data analysts to automatically extract critical information from Chinese Electronic Health Records (CEHRs). It takes unstructured CEHR text as input and identifies specific entities like admission dates, discharge dates, or diagnoses, even when they overlap within the text. The output is structured data with identified entities, their types, and locations, which can then be used for analysis or database entry.
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Use this if you need to accurately identify and extract specific, possibly overlapping, medical entities from Chinese clinical notes or patient records for research, data management, or clinical decision support.
Not ideal if your primary need is for English language records or if you are looking for a pre-trained solution that doesn't require you to prepare your own dataset and queries.
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Language
Python
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Last pushed
Oct 20, 2021
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