When a graph is poorer than 100 words: A comparison of computerised natural language generation, human generated descriptions and graphical displays in neonatal intensive care
TLDR
It is suggested that NLG might offer a viable automated approach to removing noise and artefacts in real, complex and dynamic data sets, thereby reducing visual complexity and mental workload, and enhancing decision-making particularly for inexperienced staff.Abstract:
Volunteer staff from a Neonatal Intensive Care Unit (NICU) were presented with sets of anonymised physiological data recorded over approximately 45 minute periods from former patients. Staff were asked to select medical/nursing actions appropriate for each of the patients whose data were displayed. Data were shown in one of three conditions (a) as multiple line graphs similar to those commonly shown on the ward, or as textual descriptions generated by (b) expert medical/nursing staff or (c) computerised natural language generation (NLG). An overall advantage was found for the human generated text, but NLG resulted in decisions that were at least as good as those for the graphical displays with which staff were familiar. It is suggested that NLG might offer a viable automated approach to removing noise and artefacts in real, complex and dynamic data sets, thereby reducing visual complexity and mental workload, and enhancing decision-making particularly for inexperienced staff. Copyright © 2008 John Wiley & Sons, Ltd.read more
Citations
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Survey of the state of the art in natural language generation: core tasks, applications and evaluation
Albert Gatt,Emiel Krahmer +1 more
TL;DR: A survey of the state of the art in natural language generation can be found in this article, with an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organized.
Journal ArticleDOI
Automatic generation of textual summaries from neonatal intensive care data
François Portet,Ehud Reiter,Albert Gatt,Jim Hunter,Somayajulu Sripada,Yvonne Freer,Cindy Sykes +6 more
TL;DR: A prototype, called BT-45, is presented, which generates textual summaries of about 45 minutes of continuous physiological signals and discrete events and brings together techniques from the different areas of signal processing, medical reasoning, knowledge engineering, and natural language generation.
Posted Content
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
Albert Gatt,Emiel Krahmer +1 more
TL;DR: An up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised is given, to highlight a number of recent research topics that have arisen partly as a result of growing synergies betweenNLG and other areas of artifical intelligence.
Journal ArticleDOI
An investigation into the validity of some metrics for automatically evaluating natural language generation systems
TL;DR: The results of two studies of how well some metrics which are popular in other areas of NLP correlate with human judgments in the domain of computer-generated weather forecasts suggest that, at least in this domain, metrics may provide a useful measure of language quality, although the evidence for this is not as strong as one would ideally like to see.
Journal ArticleDOI
Automated methods for the summarization of electronic health records
Rimma Pivovarov,Noémie Elhadad +1 more
TL;DR: This review examines work on automated summarization of electronic health record (EHR) data and in particular, individual patient record summarization with a particular focus on methods for detecting and removing redundancy, describing temporality, determining salience, accounting for missing data, and taking advantage of encoded clinical knowledge.
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