Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)

Abstract

In the drive to improve patient safety, patients in modem intensive care units are closely monitored with the generation of very large volumes of data. Unless the data are further processed, it is difficult for medical and nursing staff to assimilate what is important. It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content. Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations.

Original languageEnglish
Title of host publicationECAI 2008
Subtitle of host publicationProceedings of the 18th European Conference on Artificial Intelligence
EditorsMalik Ghallab, Constantine D. Spyropoulos, Nikos Fakotakis, Nikos Avouris
Place of PublicationAmsterdam, Netherlands
PublisherIOS Press
Pages678-682
Number of pages5
Volume178
ISBN (Print)1586038915, 978-1586038915
Publication statusPublished - 31 Jul 2008
Event18th European Conference on Artificial Intelligence (ECAI 2008) - Patras, Greece
Duration: 21 Jul 200825 Jul 2008

Conference

Conference18th European Conference on Artificial Intelligence (ECAI 2008)
CountryGreece
CityPatras
Period21/07/0825/07/08

Cite this

Hunter, J., Gatt, A., Portet, F., Reiter, E. B., & Sripada, G. S. (2008). Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units. In M. Ghallab, C. D. Spyropoulos, N. Fakotakis, & N. Avouris (Eds.), ECAI 2008: Proceedings of the 18th European Conference on Artificial Intelligence (Vol. 178, pp. 678-682). Amsterdam, Netherlands: IOS Press.

Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units. / Hunter, Jim; Gatt, Albert; Portet, Francois; Reiter, Ehud Baruch; Sripada, Gowri Somayajulu.

ECAI 2008: Proceedings of the 18th European Conference on Artificial Intelligence. ed. / Malik Ghallab; Constantine D. Spyropoulos; Nikos Fakotakis; Nikos Avouris. Vol. 178 Amsterdam, Netherlands : IOS Press, 2008. p. 678-682.

Research output: Chapter in Book/Report/Conference proceedingChapter

Hunter, J, Gatt, A, Portet, F, Reiter, EB & Sripada, GS 2008, Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units. in M Ghallab, CD Spyropoulos, N Fakotakis & N Avouris (eds), ECAI 2008: Proceedings of the 18th European Conference on Artificial Intelligence. vol. 178, IOS Press, Amsterdam, Netherlands, pp. 678-682, 18th European Conference on Artificial Intelligence (ECAI 2008) , Patras, Greece, 21/07/08.
Hunter J, Gatt A, Portet F, Reiter EB, Sripada GS. Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units. In Ghallab M, Spyropoulos CD, Fakotakis N, Avouris N, editors, ECAI 2008: Proceedings of the 18th European Conference on Artificial Intelligence. Vol. 178. Amsterdam, Netherlands: IOS Press. 2008. p. 678-682
Hunter, Jim ; Gatt, Albert ; Portet, Francois ; Reiter, Ehud Baruch ; Sripada, Gowri Somayajulu. / Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units. ECAI 2008: Proceedings of the 18th European Conference on Artificial Intelligence. editor / Malik Ghallab ; Constantine D. Spyropoulos ; Nikos Fakotakis ; Nikos Avouris. Vol. 178 Amsterdam, Netherlands : IOS Press, 2008. pp. 678-682
@inbook{2e9af01a1f724e87adbd41cfbe68fb03,
title = "Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units",
abstract = "In the drive to improve patient safety, patients in modem intensive care units are closely monitored with the generation of very large volumes of data. Unless the data are further processed, it is difficult for medical and nursing staff to assimilate what is important. It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content. Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations.",
author = "Jim Hunter and Albert Gatt and Francois Portet and Reiter, {Ehud Baruch} and Sripada, {Gowri Somayajulu}",
year = "2008",
month = "7",
day = "31",
language = "English",
isbn = "1586038915",
volume = "178",
pages = "678--682",
editor = "Malik Ghallab and Spyropoulos, {Constantine D.} and Fakotakis, { Nikos} and Nikos Avouris",
booktitle = "ECAI 2008",
publisher = "IOS Press",

}

TY - CHAP

T1 - Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units

AU - Hunter, Jim

AU - Gatt, Albert

AU - Portet, Francois

AU - Reiter, Ehud Baruch

AU - Sripada, Gowri Somayajulu

PY - 2008/7/31

Y1 - 2008/7/31

N2 - In the drive to improve patient safety, patients in modem intensive care units are closely monitored with the generation of very large volumes of data. Unless the data are further processed, it is difficult for medical and nursing staff to assimilate what is important. It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content. Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations.

AB - In the drive to improve patient safety, patients in modem intensive care units are closely monitored with the generation of very large volumes of data. Unless the data are further processed, it is difficult for medical and nursing staff to assimilate what is important. It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content. Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations.

M3 - Chapter

SN - 1586038915

SN - 978-1586038915

VL - 178

SP - 678

EP - 682

BT - ECAI 2008

A2 - Ghallab, Malik

A2 - Spyropoulos, Constantine D.

A2 - Fakotakis, Nikos

A2 - Avouris, Nikos

PB - IOS Press

CY - Amsterdam, Netherlands

ER -