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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Summarising complex ICU data in natural language
Jim Hunter1, Yvonne Freer, Albert Gatt
1Department of Computing Science, University of Aberdeen, UK.
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.
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