fordai/CCKS2019-Chinese-Clinical-NER
The word2vec-BiLSTM-CRF model for CCKS2019 Chinese clinical named entity recognition.
This tool helps medical professionals or researchers automatically identify key clinical entities within Chinese medical texts. You provide raw Chinese clinical documents, and it extracts and labels specific information like diseases, diagnoses, imaging results, lab tests, surgeries, medications, and anatomical parts. This is useful for anyone needing to quickly structure unstructured clinical notes or reports in Chinese.
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Use this if you need to automatically extract and categorize clinical entities from large volumes of Chinese medical text.
Not ideal if your clinical texts are in a language other than Chinese or if you require extremely high precision for highly sensitive clinical decision-making without human oversight.
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Language
Python
License
MIT
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Last pushed
Sep 05, 2019
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