NLP for Clinical Data Analysis: Handling the Unstructured Clinical Information

View Sample PDF

Author(s): Partha Sarathy Banerjee (National Institute of Technology, Durgapur, India)and Jaya Banerjee (National Institute of Technology, Durgapur, India)
Copyright: 2020
Pages: 9
Source title: Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering
Source Author(s)/Editor(s): Dilip Singh Sisodia (National Institute of Technology, Raipur, India), Ram Bilas Pachori (Indian Institute of Technology, Indore, India)and Lalit Garg (University of Malta, Malta)
DOI: 10.4018/978-1-7998-2120-5.ch018

Keywords: Artificial Intelligence / Computer Science & IT / Medical Information Science Reference / Medical Technologies

Purchase

View NLP for Clinical Data Analysis: Handling the Unstructured Clinical Information on the publisher's website for pricing and purchasing information.

Abstract

This work focuses on the topic of natural language processing for clinical data analysis. In a world where information is being generated at an exponential rate, the need for this information handling and management finds wide attention. The majority of the data being generated is in the form of unstructured data. The processing of structured information is relatively easier as compared to semi-structured or unstructured data. In the case of clinical data, the larger chunk is in unstructured form like the patient's case study and history. This chapter will provide a deeper insight into this class of data and will provide various solutions to how this data can be interpreted and represented for better healthcare of the common masses. In this chapter, the authors discuss a generic system developed for unstructured data handling: Natural Language Information Interpretation and Representation System (NLIIRS).

The IRMA Community

Research IRM

NLP for Clinical Data Analysis: Handling the Unstructured Clinical Information

Purchase

Abstract

Related Content

IRMA Sponsors