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Title: From data to text in the neonatal intensive care unit : using NLG technology for decision support and information management
Authors: Gatt, Albert
Portet, Francois
Reiter, Ehud
Hunter, Jim
Mahamood, Saad
Moncur, Wendy
Sripada, Somayajulu
Keywords: Natural language processing (Computer science)
Signal processing
Expert systems (Computer science)
Medical informatics
Issue Date: 2009
Publisher: IOS Press
Citation: Gatt, A., Portet, F., Reiter, E., Hunter, J., Mahamood, S., Moncur, W., & Sripada, S. (2009). From data to text in the neonatal intensive care unit: using NLG technology for decision support and information management. Ai Communications, 22(3), 153-186.
Abstract: Contemporary Neonatal Intensive Care Units collect vast amounts of patient data in various formats, making efficient processing of information by medical professionals difficult. Moreover, different stakeholders in the neonatal scenario, which include parents as well as staff occupying different roles, have different information requirements. This paper describes recent and ongoing work on building systems that automatically generate textual summaries of neonatal data. Our evaluation results show that the technology is viable and comparable in its effectiveness for decision support to existing presentation modalities. We discuss the lessons learned so far, as well as the major challenges involved in extending current technology to deal with a broader range of data types, and to improve the textual output in the form of more coherent summaries.
Appears in Collections:Scholarly Works - InsLin

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