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Effective presentation of data for decision support is a major issue when large volumes\ud of data are generated as happens in the Intensive Care Unit (ICU). Although the most\ud common approach is to present the data graphically, it has been shown that textual\ud summarisation can lead to improved decision making. As part of the BabyTalk project,\ud we present a prototype, called BT-45, which generates textual summaries of about 45\ud minutes of continuous physiological signals and discrete events (e.g.: equipment settings\ud and drug administration). Its architecture brings together techniques from the different\ud areas of signal processing, medical reasoning, knowledge engineering, and natural language\ud generation. A clinical off-ward experiment in a Neonatal ICU (NICU) showed that human\ud expert textual descriptions of NICU data lead to better decision making than classical\ud graphical visualisation, whereas texts generated by BT-45 lead to similar quality decisionmaking\ud as visualisations. Textual analysis showed that BT-45 texts were inferior to human\ud expert texts in a number of ways, including not reporting temporal information as well\ud and not producing good narratives. Despite these deficiencies, our work shows that it\ud is possible for computer systems to generate effective textual summaries of complex\ud continuous and discrete temporal clinical data.peer-reviewe

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.

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