Abstract:
:The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on the de-identification of longitudinal medical records. For this track, we de-identified a set of 1304 longitudinal medical records describing 296 patients. This corpus was de-identified under a broad interpretation of the HIPAA guidelines using double-annotation followed by arbitration, rounds of sanity checking, and proof reading. The average token-based F1 measure for the annotators compared to the gold standard was 0.927. The resulting annotations were used both to de-identify the data and to set the gold standard for the de-identification track of the 2014 i2b2/UTHealth shared task. All annotated private health information were replaced with realistic surrogates automatically and then read over and corrected manually. The resulting corpus is the first of its kind made available for de-identification research. This corpus was first used for the 2014 i2b2/UTHealth shared task, during which the systems achieved a mean F-measure of 0.872 and a maximum F-measure of 0.964 using entity-based micro-averaged evaluations.
journal_name
J Biomed Informjournal_title
Journal of biomedical informaticsauthors
Stubbs A,Uzuner Ödoi
10.1016/j.jbi.2015.07.020subject
Has Abstractpub_date
2015-12-01 00:00:00pages
S20-9eissn
1532-0464issn
1532-0480pii
S1532-0464(15)00182-3journal_volume
58 Supplpub_type
杂志文章abstract:OBJECTIVES:Major adverse cardiac events (MACE) of acute coronary syndrome (ACS) often occur suddenly resulting in high mortality and morbidity. Recently, the rapid development of electronic medical records (EMR) provides the opportunity to utilize the potential of EMR to improve the performance of MACE prediction. In t...
journal_title:Journal of biomedical informatics
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更新日期:2017-02-01 00:00:00
abstract::The Strategic Health IT Advanced Research Projects (SHARP) Program, established by the Office of the National Coordinator for Health Information Technology in 2010 supports research findings that remove barriers for increased adoption of health IT. The improvements envisioned by the SHARP Area 4 Consortium (SHARPn) wi...
journal_title:Journal of biomedical informatics
pub_type: 杂志文章
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abstract::Warfarin is an effective preventative treatment for arterial and venous thromboembolism, but requires individualised dosing due to its narrow therapeutic range and high individual variation. Many machine learning techniques have been demonstrated in this domain. This study evaluated the accuracy of the most promising ...
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abstract::To extract biomedical information about bio-entities from the huge amount of biomedical literature, the first key step is recognizing their names in these literatures, which remains a challenging task due to the irregularities and ambiguities in bio-entities nomenclature. The recognition performances of the current po...
journal_title:Journal of biomedical informatics
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doi:10.1016/j.jbi.2008.01.002
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journal_title:Journal of biomedical informatics
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journal_title:Journal of biomedical informatics
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
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更新日期:2017-07-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2016.10.018
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2006.09.004
更新日期:2007-08-01 00:00:00
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journal_title:Journal of biomedical informatics
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2017.12.012
更新日期:2018-02-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 临床试验,杂志文章
doi:10.1016/j.jbi.2004.12.001
更新日期:2005-08-01 00:00:00
abstract::The major challenge in influenza vaccination is to predict vaccine efficacy. The purpose of this study was to design a model to enable successful prediction of the outcome of influenza vaccination based on real historical medical data. A non-linear neural network approach was used, and its performance compared to logi...
journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2010.04.011
更新日期:2010-10-01 00:00:00
abstract::Causal inference often relies on the counterfactual framework, which requires that treatment assignment is independent of the outcome, known as strong ignorability. Approaches to enforcing strong ignorability in causal analyses of observational data include weighting and matching methods. Effect estimates, such as the...
journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2020.103515
更新日期:2020-09-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2014.07.017
更新日期:2014-12-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2020.103380
更新日期:2020-03-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2018.07.015
更新日期:2018-09-01 00:00:00
abstract::Medical error is a leading cause of patient death in the United States. Among the different types of medical errors, harm to patients caused by doctors missing early signs of deterioration is especially challenging to address due to the heterogeneity of patients' physiological patterns. In this study, we implemented r...
journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2020.103425
更新日期:2020-07-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2016.07.019
更新日期:2017-07-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2011.11.017
更新日期:2012-04-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2009.09.005
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
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更新日期:2012-06-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2009.04.003
更新日期:2009-10-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2019.103308
更新日期:2019-12-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章,评审
doi:10.1016/j.jbi.2019.103102
更新日期:2019-02-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章,多中心研究
doi:10.1016/j.jbi.2018.03.007
更新日期:2018-05-01 00:00:00
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
doi:10.1016/j.jbi.2009.08.004
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journal_title:Journal of biomedical informatics
pub_type: 杂志文章
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更新日期:2019-07-01 00:00:00