Using Semi-Automatically Annotation System on Medical Entity Recognition

Abstract

It is more and more common that people ask questions on the web and seek suggestion before visiting medical institutions. These corpus resources may be valuable for further research on natural languages processing for Medicine. Amazon provided a service called “Amazon Comprehend Medical” that could help medical experts to extract six kinds of the important terms from the articles. In this research, we proposed a medical entity recognition model to identify ten medical entity terms. A semi-auto annotation system was also developed to extract medical entity terms from the questions. The expected result shows that the annotation system could reduce 40% labeling time and provides a tagging interface to add medical entity terms manually.