Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Guy, Divita"'
Autor:
Guy Divita, Kathleen Coale, Jonathan Camacho Maldonado, Rafael Jiménez Silva, Elizabeth Rasch
Publikováno v:
Frontiers in Digital Health, Vol 4 (2022)
This paper describes the identification of body function (BF) mentions within the clinical text within a large, national, heterogeneous corpus to highlight structural challenges presented by the clinical text. BF in clinical documents provides inform
Externí odkaz:
https://doaj.org/article/66c83de84b064f7ab388b2dc3f21e46f
Publikováno v:
BMC Research Notes, Vol 12, Iss 1, Pp 1-5 (2019)
Abstract Objective Misspellings in clinical free text present challenges to natural language processing. With an objective to identify misspellings and their corrections, we developed a prototype spelling analysis method that implements Word2Vec, Lev
Externí odkaz:
https://doaj.org/article/e234941602034698b0e9a413d7b61fcc
Autor:
Howard H, Goldman, Julia, Porcino, Guy, Divita, Ayah, Zirikly, Bart, Desmet, Maryanne, Sacco, Elizabeth, Marfeo, Christine, McDonough, Elizabeth, Rasch, Leighton, Chan
Publikováno v:
Psychiatric Services. 74:56-62
The disability determination process of the Social Security Administration's (SSA's) disability program requires assessing work-related functioning for individual claimants alleging disability due to mental impairment. This task is particularly chall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0eb361cbc20bc5fc8acf74b5d5197ebe
https://doi.org/10.1176/appi.ps.202200056
https://doi.org/10.1176/appi.ps.202200056
Autor:
Guy Divita, Doug Redd, Yijun Shao, Jennifer H. Garvin, Qing Zeng-Treitler, T. Elizabeth Workman
Publikováno v:
IEEE BigData
The field of clinical natural language processing (NLP) has been built on the analysis of clinical sublanguage characteristics. It is well recognized that not only does clinical sublanguage differ from general English (or other languages) but also cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9149d7c3a68174f12a94dae9f7385d1
https://doi.org/10.1109/bigdata50022.2020.9378203
https://doi.org/10.1109/bigdata50022.2020.9378203
Publikováno v:
IEEE BigData
Irregular spellings in clinical free text present challenges to natural language processing. A number of spelling correction tools exist, but automated spelling correction of clinical text is not a routine practice due to the risk of introducing new
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ca2374bfb6819d3a2392dd979c9b6c6
https://doi.org/10.1109/bigdata50022.2020.9377978
https://doi.org/10.1109/bigdata50022.2020.9377978
Autor:
Ayah Zirikly, Bart Desmet, Eric Fosler-Lussier, Guy Divita, Denis Newman-Griffis, Carolyn Penstein Rosé
Publikováno v:
J Am Med Inform Assoc
Objectives Normalizing mentions of medical concepts to standardized vocabularies is a fundamental component of clinical text analysis. Ambiguity—words or phrases that may refer to different concepts—has been extensively researched as part of info
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e10ccd12b219eb8f764ab0df43b81c27
https://pubmed.ncbi.nlm.nih.gov/33319905
https://pubmed.ncbi.nlm.nih.gov/33319905
Autor:
Kalpana Gupta, Andrew Redd, Judith Strymish, Sarah L. Krein, Barbara W. Trautner, Marjorie E. Carter, Danette Ko, Matthew H. Samore, Anne E. Sales, Michael Rubin, Adi V. Gundlapalli, Guy Divita
Publikováno v:
Journal of Biomedical Informatics. 71:S39-S45
Objective To develop a natural language processing pipeline to extract positively asserted concepts related to the presence of an indwelling urinary catheter in hospitalized patients from the free text of the electronic medical note. The goal is to a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab9e0a4521ec2afbdce02c013c43c9e5
https://doi.org/10.1016/j.jbi.2016.07.012
https://doi.org/10.1016/j.jbi.2016.07.012
Publikováno v:
Studies in health technology and informatics. 264
Misspellings in clinical free text present potential challenges to pharmacovigilance tasks, such as monitoring for potential ineffective treatment of drug-resistant infections. We developed a novel method using Word2Vec, Levenshtein edit distance con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::2fad8a81d5a07157c3c09ba10deeaba9
https://pubmed.ncbi.nlm.nih.gov/31437964
https://pubmed.ncbi.nlm.nih.gov/31437964
Autor:
Jamison D. Fargo, Guy Divita, Audrey L. Jones, Matthew H. Samore, Adi V. Gundlapalli, Andrew Redd, Rebecca K. Blais, Warren B. P. Pettey, Emily Brignone, Marjorie E. Carter
Publikováno v:
Medical care. 57
Background Despite national screening efforts, military sexual trauma (MST) is underreported. Little is known of racial/ethnic differences in MST reporting in the Veterans Health Administration (VHA). Objective This study aimed to compare patterns of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b52a322596d8e8a628dc3600a47f0ea0
https://pubmed.ncbi.nlm.nih.gov/31095054
https://pubmed.ncbi.nlm.nih.gov/31095054
Publikováno v:
BMC Research Notes
BMC Research Notes, Vol 12, Iss 1, Pp 1-5 (2019)
BMC Research Notes, Vol 12, Iss 1, Pp 1-5 (2019)
Objective Misspellings in clinical free text present challenges to natural language processing. With an objective to identify misspellings and their corrections, we developed a prototype spelling analysis method that implements Word2Vec, Levenshtein
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dce086dbb219f18d4303f6ba00d043a1
http://europepmc.org/articles/PMC6339425
http://europepmc.org/articles/PMC6339425