Robin-WZQ/CBLUE_CMeIE_model
CBLUE2.0-关系抽取模型，基于pytorch
This tool helps medical researchers and professionals extract key information from unstructured medical texts like textbooks, clinical notes, and patient records. It takes raw Chinese medical sentences or paragraphs as input and identifies medical entities (like diseases or treatments) and the relationships between them. The output is structured data that can be used to build a medical knowledge graph.
No commits in the last 6 months.
Use this if you need to automatically identify medical entities and their relationships within large volumes of Chinese medical text to build a knowledge base.
Not ideal if your primary goal is to extract information from non-medical texts or if you require extremely high accuracy without further model fine-tuning.
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17
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Language
Python
License
MIT
Category
Last pushed
Oct 23, 2024
Commits (30d)
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