798 research outputs found

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

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    Objective: To determine if a computer system can automatically generate a useful natural language nursing shift summary solely from an electronic patient record system, in a neonatal intensive care unit (NICU). Design: A system was built which automatically generates NICU shift summaries, using datato- text technology. The system was tested for two months in the Royal Infirmary of Edinburgh NICU. Measurements: Nurses were asked to rate the understandability, accuracy, and helpfulness of the computer-generated summaries; they were also asked for free-text comments about the summaries. Results: The nurses found the majority of the summaries to be understandable, accurate, and helpful (p < .001 for all measures). However, nurses also pointed out many deficiencies, especially with regard to extra content they wanted to see in the computer-generated summaries. Conclusions: Natural language NICU shift summaries can be automatically generated from an electronic patient record. However our proof-of-concept software needs considerable additional development work.peer-reviewe

    Making effective use of healthcare data using data-to-text technology

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    Healthcare organizations are in a continuous effort to improve health outcomes, reduce costs and enhance patient experience of care. Data is essential to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text is an important medium to make data accessible. Financial reports are produced to assess healthcare organizations on some key performance indicators to steer their healthcare delivery. Similarly, at a clinical level, data on patient status is conveyed by means of textual descriptions to facilitate patient review, shift handover and care transitions. Likewise, patients are informed about data on their health status and treatments via text, in the form of reports or via ehealth platforms by their doctors. Unfortunately, such text is the outcome of a highly labour-intensive process if it is done by healthcare professionals. It is also prone to incompleteness, subjectivity and hard to scale up to different domains, wider audiences and varying communication purposes. Data-to-text is a recent breakthrough technology in artificial intelligence which automatically generates natural language in the form of text or speech from data. This chapter provides a survey of data-to-text technology, with a focus on how it can be deployed in a healthcare setting. It will (1) give an up-to-date synthesis of data-to-text approaches, (2) give a categorized overview of use cases in healthcare, (3) seek to make a strong case for evaluating and implementing data-to-text in a healthcare setting, and (4) highlight recent research challenges.Comment: 27 pages, 2 figures, book chapte

    Using Textual Summaries to Describe a Set of Products

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    When customers are faced with the task of making a purchase in an unfamiliar product domain, it might be useful to provide them with an overview of the product set to help them understand what they can expect. In this paper we present and evaluate a method to summarise sets of products in natural language, focusing on the price range, common product features across the set, and product features that impact on price. In our study, participants reported that they found our summaries useful, but we found no evidence that the summaries influenced the selections made by participants
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