A4 Article in conference proceedings
Care Episode Retrieval – Proceedings of the 5th International Workshop on Health Text Mining and Information Analysis (Louhi)




Subtitle: Proceedings of the 5th International Workshop on Health Text Mining and Information Analysis (Louhi)
List of Authors: Moen H, Marsi E, Ginter F, Murtola L-M, Salakoski T, Salanterä S
Publication year: 2014
Book title *: Proceedings of the 5th International Workshop on Health Text Mining and Information Analysis (Louhi)
Number of pages: 9
ISBN: 978-1-937284-90-9

Abstract


The documentation of a care episode consists

of clinical notes concerning patient

care, concluded with a discharge summary.

Care episodes are stored electronically

and used throughout the health care

sector by patients, administrators and professionals

from different areas, primarily

for clinical purposes, but also for secondary

purposes such as decision support

and research. A common use case is, given

a – possibly unfinished – care episode,

to retrieve the most similar care episodes

among the records. This paper presents

several methods for information retrieval,

focusing on care episode retrieval, based

on textual similarity, where similarity is

measured through domain-specific modelling

of the distributional semantics of

words. Models include variants of random

indexing and a semantic neural network

model called word2vec. A novel method is

introduced that utilizes the ICD-10 codes

attached to care episodes to better induce

domain-specificity in the semantic model.

We report on an experimental evaluation

of care episode retrieval that circumvents

the lack of human judgements regarding

episode relevance by exploiting (1) ICD-

10 codes of care episodes and (2) semantic

similarity between their discharge summaries.

Results suggest that several of the

methods proposed outperform a state-ofthe

art search engine (Lucene) on the retrieval

task.



Last updated on 2019-29-01 at 13:31