829 research outputs found
Using NLG to Manage Information in Medical Emergencies
Peer reviewedPublisher PD
BT-Nurse : computer generation of natural language shift summaries from complex heterogeneous medical data
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
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
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
Blogging birds : Generating narratives about reintroduced species to promote public engagement
Preprin
- …