Cargando…
Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese
BACKGROUND: There is an increasing amount of unstructured medical data that can be analysed for different purposes. However, information extraction from free text data may be particularly inefficient in the presence of spelling errors. Existing approaches use string similarity methods to search for...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849162/ https://www.ncbi.nlm.nih.gov/pubmed/31711534 http://dx.doi.org/10.1186/s13326-019-0216-2 |
_version_ | 1783469150490853376 |
---|---|
author | Tissot, Hegler Dobson, Richard |
author_facet | Tissot, Hegler Dobson, Richard |
author_sort | Tissot, Hegler |
collection | PubMed |
description | BACKGROUND: There is an increasing amount of unstructured medical data that can be analysed for different purposes. However, information extraction from free text data may be particularly inefficient in the presence of spelling errors. Existing approaches use string similarity methods to search for valid words within a text, coupled with a supporting dictionary. However, they are not rich enough to encode both typing and phonetic misspellings. RESULTS: Experimental results showed a joint string and language-dependent phonetic similarity is more accurate than traditional string distance metrics when identifying misspelt names of drugs in a set of medical records written in Portuguese. CONCLUSION: We present a hybrid approach to efficiently perform similarity match that overcomes the loss of information inherit from using either exact match search or string based similarity search methods. |
format | Online Article Text |
id | pubmed-6849162 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68491622019-11-15 Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese Tissot, Hegler Dobson, Richard J Biomed Semantics Research BACKGROUND: There is an increasing amount of unstructured medical data that can be analysed for different purposes. However, information extraction from free text data may be particularly inefficient in the presence of spelling errors. Existing approaches use string similarity methods to search for valid words within a text, coupled with a supporting dictionary. However, they are not rich enough to encode both typing and phonetic misspellings. RESULTS: Experimental results showed a joint string and language-dependent phonetic similarity is more accurate than traditional string distance metrics when identifying misspelt names of drugs in a set of medical records written in Portuguese. CONCLUSION: We present a hybrid approach to efficiently perform similarity match that overcomes the loss of information inherit from using either exact match search or string based similarity search methods. BioMed Central 2019-11-12 /pmc/articles/PMC6849162/ /pubmed/31711534 http://dx.doi.org/10.1186/s13326-019-0216-2 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Tissot, Hegler Dobson, Richard Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese |
title | Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese |
title_full | Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese |
title_fullStr | Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese |
title_full_unstemmed | Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese |
title_short | Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese |
title_sort | combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in portuguese |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849162/ https://www.ncbi.nlm.nih.gov/pubmed/31711534 http://dx.doi.org/10.1186/s13326-019-0216-2 |
work_keys_str_mv | AT tissothegler combiningstringandphoneticsimilaritymatchingtoidentifymisspeltnamesofdrugsinmedicalrecordswritteninportuguese AT dobsonrichard combiningstringandphoneticsimilaritymatchingtoidentifymisspeltnamesofdrugsinmedicalrecordswritteninportuguese |