An Implementation of Natural Language Processing and Text Mining in Stroke Research

Abstract

Natural language processing (NLP) is a computerized approach to analyzing text that explores how computers can be used to understand and manipulate natural language text or speech to do useful things. In healthcare field, these NLP techniques are applied in a variety of applications, ranging from evaluating the adequacy of treatment, assessing the presence of the acute illness, and the other clinical decision support. After converting text into computer-readable data through the text preprocessing process, an NLP can extract valuable information using the rule-based algorithm, machine learning, and neural network. We can use NLP to distinguish subtypes of stroke or accurately extract critical clinical information such as severity of stroke and prognosis of patients, etc. If these NLP methods are actively utilized in the future, they will be able to make the most of the electronic health records to enable optimal medical judgment.