Zeng Q, Cimino J J
Department of Medical Informatics, Columbia University, New York, New York, USA.
Proc AMIA Symp. 1998:568-72.
This paper presents our work in extracting disease-chemical relationship knowledge from the UMLS Co-occurrence table (MRCOC) using an automated method. We evaluated the quality of the knowledge from UMLS MRCOC by comparing it with knowledge from other sources: For disease-lab chemical relationships, knowledge was obtained from a decision support system (DXplain) and our own knowledge base of medical terminology (MED) through automated processes. For disease-drug chemical relationships, knowledge was manually acquired from the medical literature. Evaluations showed that the UMLS MRCOC knowledge has good sensitivity, especially regarding disease-drug relationships. We are using this knowledge to produce disease-specific views of patients' electronic patient record.
本文介绍了我们使用自动化方法从UMLS共现表（MRCOC）中提取疾病 - 化学关系知识的工作。我们通过将UMLS MRCOC中的知识与其他来源的知识进行比较来评估其质量：对于疾病 - 实验室化学关系，通过自动化流程从决策支持系统（DXplain）和我们自己的医学术语知识库（MED）中获取知识。对于疾病 - 药物化学关系，知识是从医学文献中手动获取的。评估表明，UMLS MRCOC知识具有良好的敏感性，特别是在疾病 - 药物关系方面。我们正在使用这些知识来生成患者电子病历的疾病特定视图。
