Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Stephane M Meystre"'
Autor:
Megha Kalsy, Natalie Kelly, Stephane M. Meystre, Youngjun Kim, Bruce E. Bray, Dan Bolton, Mary K. Goldstein, Jennifer H. Garvin
Publikováno v:
SAGE Open, Vol 10 (2020)
We sought to evaluate the context of potential implementation of an automated quality measurement system for inpatients with heart failure in the U.S. Department of Veterans Affairs (VA). The research methodology was guided by the Promoting Action on
Externí odkaz:
https://doaj.org/article/136ab37daa16471f8dedb7c2769aeba4
Autor:
Paul M Heider, Stéphane M Meystre
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e55676 (2024)
BackgroundClinical natural language processing (NLP) researchers need access to directly comparable evaluation results for applications such as text deidentification across a range of corpus types and the means to easily test new systems or corpora w
Externí odkaz:
https://doaj.org/article/45ef4158887d4b9ea84575c2eed3bc82
Publikováno v:
Health Informatics ISBN: 9783319987781
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20b5520ffbabacccf2b356d292226786
https://doi.org/10.1007/978-3-319-98779-8_8
https://doi.org/10.1007/978-3-319-98779-8_8
Autor:
Jennifer Hornung Garvin, Youngjun Kim, Glenn Temple Gobbel, Michael E Matheny, Andrew Redd, Bruce E Bray, Paul Heidenreich, Dan Bolton, Julia Heavirland, Natalie Kelly, Ruth Reeves, Megha Kalsy, Mary Kane Goldstein, Stephane M Meystre
BACKGROUND We developed an accurate, stakeholder-informed, automated, natural language processing (NLP) system to measure the quality of heart failure (HF) inpatient care, and explored the potential for adoption of this system within an integrated he
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8931711c323fa5532c911374983aab8a
https://doi.org/10.2196/preprints.9150
https://doi.org/10.2196/preprints.9150
Publikováno v:
Studies in health technology and informatics. 192
The past decade has witnessed an increased interest in what are called "medically unexplained syndromes" (MUS). We address the question of whether structuring the domain knowledge for MUS can be achieved by applying the principles of Ontological Real
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::b2ecc6763629bbcac193a7d37f49d57c
https://pubmed.ncbi.nlm.nih.gov/23920523
https://pubmed.ncbi.nlm.nih.gov/23920523