Clinical Text Analysis Using Interactive Natural Language Processing

Abstract

Natural Language Processing (NLP) systems are typically developed by informaticists skilled in machine learning techniques that are unfamiliar to end-users. Although NLP has been widely used in extracting information from clinical text, current systems generally do not provide any provisions for incorporating feedback and revising models based on input from domain experts. The goal of this research is to close this gap by building highly-usable tools suitable for the analysis of free text reports.