127 related articles for article (PubMed ID: 28335044)
1. Semi-automated De-identification of German Content Sensitive Reports for Big Data Analytics.
Seuss H; Dankerl P; Ihle M; Grandjean A; Hammon R; Kaestle N; Fasching PA; Maier C; Christoph J; Sedlmayr M; Uder M; Cavallaro A; Hammon M
Rofo; 2017 Jul; 189(7):661-671. PubMed ID: 28335044
[No Abstract] [Full Text] [Related]
2. Development and evaluation of an open source software tool for deidentification of pathology reports.
Beckwith BA; Mahaadevan R; Balis UJ; Kuo F
BMC Med Inform Decis Mak; 2006 Mar; 6():12. PubMed ID: 16515714
[TBL] [Abstract][Full Text] [Related]
3. Effects of personal identifier resynthesis on clinical text de-identification.
Yeniterzi R; Aberdeen J; Bayer S; Wellner B; Hirschman L; Malin B
J Am Med Inform Assoc; 2010; 17(2):159-68. PubMed ID: 20190058
[TBL] [Abstract][Full Text] [Related]
4. 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; 8():32. PubMed ID: 18652655
[TBL] [Abstract][Full Text] [Related]
5. De-identification of Address, Date, and Alphanumeric Identifiers in Narrative Clinical Reports.
Kayaalp M; Browne AC; Dodd ZA; Sagan P; McDonald CJ
AMIA Annu Symp Proc; 2014; 2014():767-76. PubMed ID: 25954383
[TBL] [Abstract][Full Text] [Related]
6. deidentify.
Burckhardt P; Padman R
AMIA Annu Symp Proc; 2017; 2017():485-494. PubMed ID: 29854113
[TBL] [Abstract][Full Text] [Related]
7. 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. PubMed ID: 24370391
[TBL] [Abstract][Full Text] [Related]
8. The MITRE Identification Scrubber Toolkit: design, training, and assessment.
Aberdeen J; Bayer S; Yeniterzi R; Wellner B; Clark C; Hanauer D; Malin B; Hirschman L
Int J Med Inform; 2010 Dec; 79(12):849-59. PubMed ID: 20951082
[TBL] [Abstract][Full Text] [Related]
9. De-identifying an EHR database - anonymity, correctness and readability of the medical record.
Pantazos K; Lauesen S; Lippert S
Stud Health Technol Inform; 2011; 169():862-6. PubMed ID: 21893869
[TBL] [Abstract][Full Text] [Related]
10. De-identification of primary care electronic medical records free-text data in Ontario, Canada.
Tu K; Klein-Geltink J; Mitiku TF; Mihai C; Martin J
BMC Med Inform Decis Mak; 2010 Jun; 10():35. PubMed ID: 20565894
[TBL] [Abstract][Full Text] [Related]
11. Improved de-identification of physician notes through integrative modeling of both public and private medical text.
McMurry AJ; Fitch B; Savova G; Kohane IS; Reis BY
BMC Med Inform Decis Mak; 2013 Oct; 13():112. PubMed ID: 24083569
[TBL] [Abstract][Full Text] [Related]
12. A unified framework for evaluating the risk of re-identification of text de-identification tools.
Scaiano M; Middleton G; Arbuckle L; Kolhatkar V; Peyton L; Dowling M; Gipson DS; El Emam K
J Biomed Inform; 2016 Oct; 63():174-183. PubMed ID: 27426236
[TBL] [Abstract][Full Text] [Related]
13. Structured Reporting in Clinical Routine.
Pinto Dos Santos D; Hempel JM; Mildenberger P; Klöckner R; Persigehl T
Rofo; 2019 Jan; 191(1):33-39. PubMed ID: 30103236
[TBL] [Abstract][Full Text] [Related]
14. Optimizing annotation resources for natural language de-identification via a game theoretic framework.
Li M; Carrell D; Aberdeen J; Hirschman L; Kirby J; Li B; Vorobeychik Y; Malin BA
J Biomed Inform; 2016 Jun; 61():97-109. PubMed ID: 27020263
[TBL] [Abstract][Full Text] [Related]
15. An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice.
El-Hayek C; Barzegar S; Faux N; Doyle K; Pillai P; Mutch SJ; Vaisey A; Ward R; Sanci L; Dunn AG; Hellard ME; Hocking JS; Verspoor K; Boyle DI
Int J Med Inform; 2023 May; 173():105021. PubMed ID: 36870249
[TBL] [Abstract][Full Text] [Related]
16. A De-identification method for bilingual clinical texts of various note types.
Shin SY; Park YR; Shin Y; Choi HJ; Park J; Lyu Y; Lee MS; Choi CM; Kim WS; Lee JH
J Korean Med Sci; 2015 Jan; 30(1):7-15. PubMed ID: 25552878
[TBL] [Abstract][Full Text] [Related]
17. 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(Suppl):S82-101. PubMed ID: 22692265
[TBL] [Abstract][Full Text] [Related]
18. Bootstrapping a de-identification system for narrative patient records: cost-performance tradeoffs.
Hanauer D; Aberdeen J; Bayer S; Wellner B; Clark C; Zheng K; Hirschman L
Int J Med Inform; 2013 Sep; 82(9):821-31. PubMed ID: 23643147
[TBL] [Abstract][Full Text] [Related]
19. Can physicians recognize their own patients in de-identified notes?
Meystre S; Shen S; Hofmann D; Gundlapalli A
Stud Health Technol Inform; 2014; 205():778-82. PubMed ID: 25160293
[TBL] [Abstract][Full Text] [Related]
20. 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. PubMed ID: 19482543
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
