Summarising complex ICU data in natural language

It has been shown that summarizing complex multi-channel physiological and discrete data in natural language (text) can lead to better decision-making in the intensive care unit (ICU). As part of the BabyTalk project, we describe a prototype system (BT-45) which can generate such textual summaries a...

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Published inAMIA ... Annual Symposium proceedings Vol. 2008; pp. 323 - 327
Main Authors Hunter, Jim, Freer, Yvonne, Gatt, Albert, Logie, Robert, McIntosh, Neil, van der Meulen, Marian, Portet, Francois, Reiter, Ehud, Sripada, Somayajulu, Sykes, Cindy
Format Journal Article
LanguageEnglish
Published United States American Medical Informatics Association 06.11.2008
Subjects
Critical Care - methods
Data Display
Decision Support Systems, Management - organization & administration
Diagnosis, Computer-Assisted - methods
Information Dissemination - methods
Monitoring, Physiologic - methods
Natural Language Processing
User-Computer Interface
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Abstract It has been shown that summarizing complex multi-channel physiological and discrete data in natural language (text) can lead to better decision-making in the intensive care unit (ICU). As part of the BabyTalk project, we describe a prototype system (BT-45) which can generate such textual summaries automatically. Although these summaries are not yet as good as those generated by human experts, we have demonstrated experimentally that they lead to as good decision-making as can be achieved through presenting the same data graphically.
AbstractList It has been shown that summarizing complex multi-channel physiological and discrete data in natural language (text) can lead to better decision-making in the intensive care unit (ICU). As part of the BabyTalk project, we describe a prototype system (BT-45) which can generate such textual summaries automatically. Although these summaries are not yet as good as those generated by human experts, we have demonstrated experimentally that they lead to as good decision-making as can be achieved through presenting the same data graphically.
It has been shown that summarizing complex multichannel physiological and discrete data in natural language (text) can lead to better decision-making in the intensive care unit (ICU). As part of the BabyTalk project, we describe a prototype system (BT-45) which can generate such textual summaries automatically. Although these summaries are not yet as good as those generated by human experts, we have demonstrated experimentally that they lead to as good decision-making as can be achieved through presenting the same data graphically.
Author Gatt, Albert
van der Meulen, Marian
Logie, Robert
McIntosh, Neil
Hunter, Jim
Freer, Yvonne
Portet, Francois
Reiter, Ehud
Sripada, Somayajulu
Sykes, Cindy
AuthorAffiliation 3 Department of Psychology, University of Edinburgh
1 Department of Computing Science, University of Aberdeen, UK
2 Simpson Centre for Reproductive Health, Royal Infirmary of Edinburgh and
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References 9391935 - J Am Med Inform Assoc. 1997 Nov-Dec;4(6):473-82
12695796 - Methods Inf Med. 2003;42(1):51-60
16244840 - J Clin Monit Comput. 2005 Jun;19(3):183-94
16779035 - AMIA Annu Symp Proc. 2005;:226-30
9875920 - Crit Care Med. 1998 Dec;26(12):2053-60
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SubjectTerms Critical Care - methods
Data Display
Decision Support Systems, Management - organization & administration
Diagnosis, Computer-Assisted - methods
Information Dissemination - methods
Monitoring, Physiologic - methods
Natural Language Processing
User-Computer Interface
Title Summarising complex ICU data in natural language
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