Olaronke G. Iroju

Work place: Department of Computer Science, Adeyemi College of Education, Ondo, Nigeria

E-mail: irojuolaronke@gmail.com

Website: https://www.researchgate.net/profile/Iroju-Olaronke

Research Interests: Online information processing, Information Systems, Natural Language Processing, Software Development Process

Biography

Olaronke Ganiat Iroju is a lecturer in the department of Computer Science, Adeyemi College of Education, Ondo, Ondo State, Nigeria. She bagged her M.Sc. and PhD in Computer Science at the Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria. She bagged a B.Sc. in Computer Technology at Babcock University, Ilishan Remo, Ogun State, Nigeria. Her areas of research include software development and information system.

 

Author Articles
A Systematic Review of Natural Language Processing in Healthcare

By Olaronke G. Iroju Janet O. Olaleke

DOI: https://doi.org/10.5815/ijitcs.2015.08.07, Pub. Date: 8 Jul. 2015

The healthcare system is a knowledge driven industry which consists of vast and growing volumes of narrative information obtained from discharge summaries/reports, physicians case notes, pathologists as well as radiologists reports. This information is usually stored in unstructured and non-standardized formats in electronic healthcare systems which make it difficult for the systems to understand the information contents of the narrative information. Thus, the access to valuable and meaningful healthcare information for decision making is a challenge. Nevertheless, Natural Language Processing (NLP) techniques have been used to structure narrative information in healthcare. Thus, NLP techniques have the capability to capture unstructured healthcare information, analyze its grammatical structure, determine the meaning of the information and translate the information so that it can be easily understood by the electronic healthcare systems. Consequently, NLP techniques reduce cost as well as improve the quality of healthcare. It is therefore against this background that this paper reviews the NLP techniques used in healthcare, their applications as well as their limitations.

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