A4 Artikkeli konferenssijulkaisussa
Evaluation of a Prototype System that Automatically Assigns Subject Headings to Nursing Narratives Using Recurrent Neural Network




Julkaisun tekijät: Hans Moen, Kai Hakala, Laura-Maria Peltonen, Henry Suhonen, Petri Loukasmäki, Tapio Salakoski, Filip Ginter, Sanna Salanterä
Julkaisuvuosi: 2018
Kirjan nimi *: Proceedings of the 9th International Workshop on Health Text Mining and Information Analysis (LOUHI 2018)
ISBN: 978-1-948087-74-2

Tiivistelmä

We present our initial evaluation of a prototype
system designed to assist nurses in assigning
subject headings to nursing narratives
– written in the context of documenting patient
care in hospitals. Currently nurses may need
to memorize several hundred subject headings
from standardized nursing terminologies
when structuring and assigning the right section/subject
headings to their text. Our aim is
to allow nurses to write in a narrative manner
without having to plan and structure the text
with respect to sections and subject headings,
instead the system should assist with the assignment
of subject headings and restructuring
afterwards. We hypothesize that this could
reduce the time and effort needed for nursing
documentation in hospitals. A central component
of the system is a text classification model
based on a long short-term memory (LSTM)
recurrent neural network architecture, trained
on a large data set of nursing notes. A simple
Web-based interface has been implemented for
user interaction. To evaluate the system, three
nurses write a set of artificial nursing shift
notes in a fully unstructured narrative manner,
without planning for or consider the use of
sections and subject headings. These are then
fed to the system which assigns subject headings
to each sentence and then groups them
into paragraphs. Manual evaluation is conducted
by a group of nurses. The results show
that about 70% of the sentences are assigned
to correct subject headings. The nurses believe
that such a system can be of great help
in making nursing documentation in hospitals
easier and less time consuming. Finally, various
measures and approaches for improving
the system are discussed.


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Last updated on 2019-29-01 at 14:44