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Review
. 2023;65(2):463-516.
doi: 10.1007/s10115-022-01779-1. Epub 2022 Nov 8.

Information extraction from electronic medical documents: state of the art and future research directions

Mohamed Yassine Landolsi  1 , Lobna Hlaoua  1 , Lotfi Ben Romdhane  1
Affiliations
Review

Information extraction from electronic medical documents: state of the art and future research directions

Mohamed Yassine Landolsi et al. Knowl Inf Syst. 2023.

Abstract

In the medical field, a doctor must have a comprehensive knowledge by reading and writing narrative documents, and he is responsible for every decision he takes for patients. Unfortunately, it is very tiring to read all necessary information about drugs, diseases and patients due to the large amount of documents that are increasing every day. Consequently, so many medical errors can happen and even kill people. Likewise, there is such an important field that can handle this problem, which is the information extraction. There are several important tasks in this field to extract the important and desired information from unstructured text written in natural language. The main principal tasks are named entity recognition and relation extraction since they can structure the text by extracting the relevant information. However, in order to treat the narrative text we should use natural language processing techniques to extract useful information and features. In our paper, we introduce and discuss the several techniques and solutions used in these tasks. Furthermore, we outline the challenges in information extraction from medical documents. In our knowledge, this is the most comprehensive survey in the literature with an experimental analysis and a suggestion for some uncovered directions.

Keywords: Electronic medical records; Information extraction; Medical named entities recognition; Medical relation extraction; Section detection.

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Conflict of interest statement

Conflict of interestThe authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
The general steps of the EMR data processing
See this image and copyright information in PMC

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