Automatic generation of natural language nursing shift summaries in neonatal intensive care: BT-Nurse

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Automatic generation of natural language nursing shift summaries in neonatal intensive care: BT-Nurse

INTRODUCTION Our objective was to determine whether and how a computer system could automatically generate helpful natural language nursing shift summaries solely from an electronic patient record system, in a neonatal intensive care unit (NICU). METHODS A system was developed which automatically generates partial NICU shift summaries (for the respiratory and cardiovascular systems), using da...

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BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data

The BT-Nurse system uses data-to-text technology to automatically generate a natural language nursing shift summary in a neonatal intensive care unit (NICU). The summary is solely based on data held in an electronic patient record system, no additional data-entry is required. BT-Nurse was tested for two months in the Royal Infirmary of Edinburgh NICU. Nurses were asked to rate the understandabi...

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Automatic Generation of Textual Summaries from Neonatal Intensive Care Data

Effective presentation of data for decision support is a major issue when large volumes of data are generated as happens in the Intensive Care Unit (ICU). Although the most common approach is to present the data graphically, it has been shown that textual summarisation can lead to improved decision making. As part of the BabyTalk project, we present a prototype, called BT-45, which generates te...

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Automatic Generation of Natural Language Summaries

Automatic text summarization has gained much interest in the last few years, since it could, at least in principle, make the process of information seeking in large document collections less tedious and time-consuming. Most existing summarization methods generate summaries by initially extracting the sentences that are most relevant to the user’s query from documents returned by an information ...

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BT-45: Automatic Textual Summarisation of Neonatal Intensive Care Data

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 decisions making (e.g.: for nurse handover). To facilitate this summarisation, we developed a system called BT-45 that automatically generates textual summaries from periods of continuous and discrete...

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ژورنال

عنوان ژورنال: Artificial Intelligence in Medicine

سال: 2012

ISSN: 0933-3657

DOI: 10.1016/j.artmed.2012.09.002