非结构化电子病历关系抽取的机器学习

Machine Learning From Non-structured Electronic Medical Record on Relation Extraction

目的:实现电子病历(EMR)病程记录中关系抽取的机器学习。方法:利用文本工程通用框架(GATE)的应用实例组件批处理学习进程资源(Batch learning Process Resource)进行机器学习。结果:机器学习关系抽取的结果符合预期要求,具有较好的实用性。结论:利用Batch learning PR可以在EMR大段文章中快速自动获取所需的关系信息。

Objective： Implementation of electronic medical records （EMR） of the relation extraction in the field of machine learning. Methods： Using the GATE of the application components to deal with the Batch learning PR. Results： The result of relation extraction from machine learning meets the expected requirements and has good practicability. Conclusion： Using learning Ptk Batch can quicHy and automatically get the required relation information in the EMR large section of the article.