Summarising complex ICU data in natural language: demonstration of the BT-45 system.
As ICUs generate increasing amounts of information, writing medical reports involves complex time-consuming reasoning to build a coherent text which will be meaningful to those who will use it for decision making (e.g.: for nurse handover). Moreover, 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). To facilitate this summarisation, as part of the BabyTalk project, we have developed a system called BT-45 that automatically generates textual summaries from periods of continuous and discrete data in a neonatal ICU. The demonstration will show the system running on real data and will detail the steps in the construction of the final text. 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.
Portet
François
F
Department of Computing Science, University of Aberdeen, UK.
Gatt
Albert
A
Reiter
Ehud
E
Hunter
Jim
J
Sripada
Somayajulu
S
Sykes
Cindy
C
Freer
Yvonne
Y
McIntosh
Neil
N
van der Meulen
Marian
M
Logie
Robert
R
D000465:Algorithms; D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical; D016247:Information Storage and Retrieval / Q000379:methods; D007363:Intensive Care Units, Neonatal; D008487:Medical History Taking / Q000379:methods*; D008498:Medical Record Linkage; D016347:Medical Records Systems, Computerized; D008991:Monitoring, Physiologic / Q000379:methods*; D009323:Natural Language Processing; D006113:United Kingdom