IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Analysing Clinical Notes for Translation Research: Back to the Future

Analysing Clinical Notes for Translation Research: Back to the Future
View Sample PDF
Author(s): Jon Patrick (The University of Sydney, Australia)and Pooyan Asgari (The University of Sydney, Australia)
Copyright: 2009
Pages: 21
Source title: Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration
Source Author(s)/Editor(s): Violaine Prince (University Montpellier 2, France)and Mathieu Roche (University Montpellier 2, France)
DOI: 10.4018/978-1-60566-274-9.ch020

Purchase

View Analysing Clinical Notes for Translation Research: Back to the Future on the publisher's website for pricing and purchasing information.

Abstract

There have been few studies of large corpora of narrative notes collected from the health clinicians working at the point of care. This chapter describes the principle issues in analysing a corpus of 44 million words of clinical notes drawn from the Intensive Care Service of a Sydney hospital. The study identifies many of the processing difficulties in dealing with written materials that have a high degree of informality, written in circumstances where the authors are under significant time pressures, and containing a large technical lexicon, in contrast to formally published material. Recommendations on the processing tasks needed to turn such materials into a more usable form are provided. The chapter argues that these problems require a return to issues of 30 years ago that have been mostly solved for computational linguists but need to be revisited for this entirely new genre of materials. In returning to the past and studying the contents of these materials in retrospective studies we can plan to go forward to a future that provides technologies that better support clinicians. They need to produce both lexically and grammatically higher quality texts that can then be leveraged successfully for advanced translational research thereby bolstering its momentum.

Related Content

Linkon Chowdhury, Md Sarwar Kamal, Shamim H. Ripon, Sazia Parvin, Omar Khadeer Hussain, Amira Ashour, Bristy Roy Chowdhury. © 2024. 20 pages.
Mousomi Roy. © 2024. 21 pages.
Nassima Dif, Zakaria Elberrichi. © 2024. 20 pages.
Pyingkodi Maran, Shanthi S., Thenmozhi K., Hemalatha D., Nanthini K.. © 2024. 16 pages.
Mohamed Nadjib Boufenara, Mahmoud Boufaida, Mohamed Lamine Berkane. © 2024. 16 pages.
Meroua Daoudi, Souham Meshoul, Samia Boucherkha. © 2024. 25 pages.
Zhongyu Lu, Qiang Xu, Murad Al-Rajab, Lamogha Chiazor. © 2024. 56 pages.
Body Bottom