beader/ruijin_round2

瑞金医院MMC人工智能辅助构建知识图谱大赛复赛

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This project helps medical professionals or researchers automatically identify specific relationships between medical entities within unstructured clinical text, such as patient notes or research papers. It takes medical text where entities like 'Disease' or 'Drug Name' have already been identified, and outputs a structured list of relationships, like 'Symptom_Disease' or 'Test_Disease'. This is ideal for medical information specialists or clinical researchers who need to extract structured data from large volumes of medical reports.

181 stars. No commits in the last 6 months.

Use this if you need to automatically extract defined relationships between known medical entities from Chinese clinical texts.

Not ideal if you need to identify medical entities themselves (like diseases or symptoms) before extracting relationships, or if your texts are in a language other than Chinese.

clinical-research medical-informatics knowledge-graph-construction medical-text-analysis healthcare-data-extraction
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 22 / 25

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Last pushed

May 15, 2019

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