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Items: 1 to 20 of 141

1.

Generalizability and comparison of automatic clinical text de-identification methods and resources.

Ferrández Ó, South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM.

AMIA Annu Symp Proc. 2012;2012:199-208. Epub 2012 Nov 3.

2.

Evaluating current automatic de-identification methods with Veteran's health administration clinical documents.

Ferrández O, South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM.

BMC Med Res Methodol. 2012 Jul 27;12:109.

3.

BoB, a best-of-breed automated text de-identification system for VHA clinical documents.

Ferrández O, South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM.

J Am Med Inform Assoc. 2013 Jan 1;20(1):77-83. doi: 10.1136/amiajnl-2012-001020. Epub 2012 Sep 4.

4.

Text de-identification for privacy protection: a study of its impact on clinical text information content.

Meystre SM, Ferrández Ó, Friedlin FJ, South BR, Shen S, Samore MH.

J Biomed Inform. 2014 Aug;50:142-50. doi: 10.1016/j.jbi.2014.01.011. Epub 2014 Feb 3.

5.

Automated de-identification of free-text medical records.

Neamatullah I, Douglass MM, Lehman LW, Reisner A, Villarroel M, Long WJ, Szolovits P, Moody GB, Mark RG, Clifford GD.

BMC Med Inform Decis Mak. 2008 Jul 24;8:32. doi: 10.1186/1472-6947-8-32.

6.

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

Meystre SM, Friedlin FJ, South BR, Shen S, Samore MH.

BMC Med Res Methodol. 2010 Aug 2;10:70. doi: 10.1186/1471-2288-10-70. Review.

7.

Preparing an annotated gold standard corpus to share with extramural investigators for de-identification research.

Deleger L, Lingren T, Ni Y, Kaiser M, Stoutenborough L, Marsolo K, Kouril M, Molnar K, Solti I.

J Biomed Inform. 2014 Aug;50:173-83. doi: 10.1016/j.jbi.2014.01.014. Epub 2014 Feb 17.

8.

Evaluating the effects of machine pre-annotation and an interactive annotation interface on manual de-identification of clinical text.

South BR, Mowery D, Suo Y, Leng J, Ferrández Ó, Meystre SM, Chapman WW.

J Biomed Inform. 2014 Aug;50:162-72. doi: 10.1016/j.jbi.2014.05.002. Epub 2014 May 20.

9.

Evaluating the state-of-the-art in automatic de-identification.

Uzuner O, Luo Y, Szolovits P.

J Am Med Inform Assoc. 2007 Sep-Oct;14(5):550-63. Epub 2007 Jun 28.

10.

De-identification of health records using Anonym: effectiveness and robustness across datasets.

Zuccon G, Kotzur D, Nguyen A, Bergheim A.

Artif Intell Med. 2014 Jul;61(3):145-51. doi: 10.1016/j.artmed.2014.03.006. Epub 2014 Apr 3.

PMID:
24791676
11.

Strategies for maintaining patient privacy in i2b2.

Murphy SN, Gainer V, Mendis M, Churchill S, Kohane I.

J Am Med Inform Assoc. 2011 Dec;18 Suppl 1:i103-8. doi: 10.1136/amiajnl-2011-000316. Epub 2011 Oct 7.

12.

State-of-the-art anonymization of medical records using an iterative machine learning framework.

Szarvas G, Farkas R, Busa-Fekete R.

J Am Med Inform Assoc. 2007 Sep-Oct;14(5):574-80. Erratum in: J Am Med Inform Assoc. 2009 May-Jun;16(3):284.

13.

Proposal and evaluation of FASDIM, a Fast And Simple De-Identification Method for unstructured free-text clinical records.

Chazard E, Mouret C, Ficheur G, Schaffar A, Beuscart JB, Beuscart R.

Int J Med Inform. 2014 Apr;83(4):303-12. doi: 10.1016/j.ijmedinf.2013.11.005. Epub 2013 Dec 7.

PMID:
24370391
14.

Assessing the difficulty and time cost of de-identification in clinical narratives.

Dorr DA, Phillips WF, Phansalkar S, Sims SA, Hurdle JF.

Methods Inf Med. 2006;45(3):246-52.

PMID:
16685332
15.

Strategies for de-identification and anonymization of electronic health record data for use in multicenter research studies.

Kushida CA, Nichols DA, Jadrnicek R, Miller R, Walsh JK, Griffin K.

Med Care. 2012 Jul;50 Suppl:S82-101. doi: 10.1097/MLR.0b013e3182585355. Review.

PMID:
22692265
16.

Developing a standard for de-identifying electronic patient records written in Swedish: precision, recall and F-measure in a manual and computerized annotation trial.

Velupillai S, Dalianis H, Hassel M, Nilsson GH.

Int J Med Inform. 2009 Dec;78(12):e19-26. doi: 10.1016/j.ijmedinf.2009.04.005. Epub 2009 May 23.

PMID:
19482543
17.

A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries.

Jiang M, Chen Y, Liu M, Rosenbloom ST, Mani S, Denny JC, Xu H.

J Am Med Inform Assoc. 2011 Sep-Oct;18(5):601-6. doi: 10.1136/amiajnl-2011-000163. Epub 2011 Apr 20.

18.

Inductive creation of an annotation schema and a reference standard for de-identification of VA electronic clinical notes.

Mayer J, Shen S, South BR, Meystre S, Friedlin FJ, Ray WR, Samore M.

AMIA Annu Symp Proc. 2009 Nov 14;2009:416-20.

19.

De-identification of clinical notes in French: towards a protocol for reference corpus development.

Grouin C, Névéol A.

J Biomed Inform. 2014 Aug;50:151-61. doi: 10.1016/j.jbi.2013.12.014. Epub 2013 Dec 29.

20.
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