beader/ruijin_round1
瑞金医院MMC人工智能辅助构建知识图谱大赛初赛
This project helps medical professionals and researchers automatically identify and extract key information from diabetes-related medical literature, such as textbooks and research papers. It takes unstructured medical text as input and outputs structured annotations for 15 specific entity types, including diseases, symptoms, treatments, and drug dosages. It's designed for medical domain experts who need to build or populate a knowledge graph about diabetes.
142 stars. No commits in the last 6 months.
Use this if you need to quickly and accurately extract structured medical entities from large volumes of unstructured Chinese medical text related to diabetes.
Not ideal if your medical text is in a language other than Chinese, or if your focus is on medical domains outside of diabetes.
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Last pushed
May 28, 2019
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