Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Laura Stoutenborough"'
Autor:
Todd Lingren, Yizhao Ni, Megan Kaiser, Keith Marsolo, Imre Solti, Laura Stoutenborough, Louise Deléger, Katalin Molnar, Michal Kouril
Publikováno v:
Journal of Biomedical Informatics. 50:173-183
Objective The current study aims to fill the gap in available healthcare de-identification resources by creating a new sharable dataset with realistic Protected Health Information (PHI) without reducing the value of the data for de-identification res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdb5b5bd6148868b9c38ac46c32458bf
Autor:
Haijun Zhai, Eric S. Hall, Kristin R. Melton, Laura Stoutenborough, Todd Lingren, Eric S. Kirkendall, Qi Li, Imre Solti, Yizhao Ni, Megan Kaiser
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Background Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb595728d5aa9a2908a38710778f3c33
http://europepmc.org/articles/PMC4147599
http://europepmc.org/articles/PMC4147599
Autor:
Imre Solti, Megan Kaiser, Qi Li, Todd Lingren, Louise Deléger, Haijun Zhai, Katalin Molnar, Laura Stoutenborough, Jareen Meinzen-Derr
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Objective To present a series of experiments: (1) to evaluate the impact of pre-annotation on the speed of manual annotation of clinical trial announcements; and (2) to test for potential bias, if pre-annotation is utilized. Methods To build the gold
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::184cbf4dce873a85cb2c0ab1e6c919cb
http://europepmc.org/articles/PMC3994857
http://europepmc.org/articles/PMC3994857
Autor:
Megan Kaiser, Todd Lingren, Qi Li, Keith Marsolo, Anil G. Jegga, Laura Stoutenborough, Guergana Savova, Fei Xia, Louise Deléger, Katalin Molnar, Imre Solti
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Objective (1) To evaluate a state-of-the-art natural language processing (NLP)-based approach to automatically de-identify a large set of diverse clinical notes. (2) To measure the impact of de-identification on the performance of information extract
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27913d6ada76283a46e0952f1cf43b18
https://doi.org/10.1136/amiajnl-2012-001012
https://doi.org/10.1136/amiajnl-2012-001012
Autor:
Todd Lingren, Imre Solti, Laura Stoutenborough, Megan Kaiser, Qi Li, Haijun Zhai, Louise Deléger
Publikováno v:
Journal of Medical Internet Research
Journal of Medical Internet Research, Vol 15, Iss 4, p e73 (2013)
Journal of Medical Internet Research, Vol 15, Iss 4, p e73 (2013)
Background: A high-quality gold standard is vital for supervised, machine learning-based, clinical natural language processing (NLP) systems. In clinical NLP projects, expert annotators traditionally create the gold standard. However, traditional ann
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::519a436ac4e6de5baf78237b9f77a0b9
http://europepmc.org/articles/PMC3636329
http://europepmc.org/articles/PMC3636329
Autor:
Megan Kaiser, Laura Stoutenborough, Imre Solti, Todd Lingren, Qi Li, Haijun Zhai, Louise Deléger
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Objective The goal of this work was to evaluate machine learning methods, binary classification and sequence labeling, for medication–attribute linkage detection in two clinical corpora. Data and methods We double annotated 3000 clinical trial anno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1acef45872cb10c244f81e1bd13dee2
https://pubmed.ncbi.nlm.nih.gov/23268488
https://pubmed.ncbi.nlm.nih.gov/23268488
Autor:
Todd Lingren, Qi Li, Megan Kaiser, Laura Stoutenborough, Imre Solti, Louise Deléger, Haijun Zhai
Publikováno v:
HISB
Building upon previous work from the general crowdsourcing research, this study investigates the usability of crowdsourcing in the clinical NLP domain for annotating medical named entities and entity linkages in a clinical trial announcement (CTA) co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff50abe1a9970af8f1f472d0131df04c
https://doi.org/10.1109/hisb.2012.31
https://doi.org/10.1109/hisb.2012.31
Autor:
Megan Kaiser, Imre Solti, Jareen Meinzen-Derr, Louise Deléger, Katalin Molnar, Todd Lingren, Haijun Zhai, Qi Li, Laura Stoutenborough
Publikováno v:
HISB
In this study our aim was to present a series of experiments to evaluate the impact of pre-annotation: (1) on the speed of manual annotation of clinical notes and clinical trial announcements; and (2) test for potential bias if pre-annotation is util
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14332907211f31a027f560a3ebc3def5
https://doi.org/10.1109/hisb.2012.33
https://doi.org/10.1109/hisb.2012.33
Autor:
Lee, Ji-Ung1 (AUTHOR) lee@ukp.informatik.tu-darmstadt.de, Klie, Jan-Christoph1 (AUTHOR) klie@ukp.informatik.tu-darmstadt.de, Gurevych, Iryna1 (AUTHOR) gurevych@ukp.informatik.tu-darmstadt.de
Publikováno v:
Computational Linguistics. 6/9/2022, Vol. 48 Issue 2, p343-373. 31p.
Publikováno v:
2012 IEEE Second International Conference on Healthcare Informatics, Imaging & Systems Biology; 1/ 1/2012, pv-x, 6p