Clinical Decision Support Systems: A Survey of NLP-Based Approaches from Unstructured Data

Abstract

Clinical Decision Support on patients health outcomes can be performed from free text with Natural Language Processing techniques. However, it becomes a computational challenge due to the complexity of natural language. In recent years, several NLP-based approaches have been proposed to consider clinical decisions support. This paper presents a survey of Natural Language Processing approaches to support clinical decisions on patient health outcomes. The presented approaches are emphasized on the use of free text as input for diverse languages. An analysis of clinical decision support systems based on natural language processing in terms of their performance results is presented.