Information Extraction in the Medical Domain

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Author(s): Aicha Ghoulam (University of Oran 1, Ahmed Ben Bella, Algeria), Fatiha Barigou (University of Oran 1, Ahmed Ben Bella, Algeria)and Ghalem Belalem (University of Oran 1, Ahmed Ben Bella, Algeria)
Copyright: 2017
Pages: 18
Source title: Artificial Intelligence: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1759-7.ch075

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

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Abstract

Information Extraction (IE) is a natural language processing (NLP) task whose aim is to analyse texts written in natural language to extract structured and useful information such as named entities and semantic relations between them. Information extraction is an important task in a diverse set of applications like bio-medical literature mining, customer care, community websites, personal information management and so on. In this paper, the authors focus only on information extraction from clinical reports. The two most fundamental tasks in information extraction are discussed; namely, named entity recognition task and relation extraction task. The authors give details about the most used rule/pattern-based and machine learning techniques for each task. They also make comparisons between these techniques and summarize the advantages and disadvantages of each one.

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