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Summarising Complex ICU Data in Natural Language

By Jim Hunter, Yvonne Freer, Albert Gatt, Robert Logie, Neil McIntosh, Marian van der Meulen, François Portet, Ehud Reiter, Somayajulu Sripada and Cindy Sykes

Abstract

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

Topics: Articles
Publisher: American Medical Informatics Association
OAI identifier: oai:pubmedcentral.nih.gov:2656014
Provided by: PubMed Central
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