A Data Protection by Design Model for Privacy Management in Electronic Health Records
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Natural language processing methods have shown their usefulness for extraction of structured clinical data from unstructured data elements.
“Natural language processing (NLP) methods have shown their usefulness for extraction of structured clinical data from unstructured data elements [36], [37].”
From Secondary Use of Electronic Health Record: Opportunities and Challenges (2020) · cites this paper as [36]
Natural language processing (NLP) methods have shown their usefulness for extraction of structured clinical data from unstructured data elements.
“Natural language processing (NLP) methods have shown their usefulness for extraction of structured clinical data from unstructured data elements[36],[37].”
From Secondary Use of Electronic Health Record: Opportunities and Challenges (2020) · cites this paper as [36]
Cites
The EU General Data Protection Regulation (GDPR)
Voigt, P., & von dem Bussche, A. (2017) · doi:10.1007/978-3-319-57959-7 · Cited by 3,001 · see citing works
The FTC and the New Common Law of PrivacyPreprint
Solove, D. J., & Hartzog, W. (2013) · SSRN Electronic Journal · doi:10.2139/ssrn.2312913 · Cited by 178 · see citing works
Privacy by design: the definitive workshop. A foreword by Ann Cavoukian, Ph.D
Cavoukian, A. (2010) · Identity in the Information Society · doi:10.1007/s12394-010-0062-y · Cited by 152 · see citing works
A Critical Analysis of Privacy Design Strategies
Colesky, M., Hoepman, J.-H., & Hillen, C. (2016) · IEEE Security and Privacy Workshops (SPW) · doi:10.1109/spw.2016.23 · Cited by 143 · see citing works
Data Protection by Design and by Default : Deciphering the EU’s Legislative Requirements
Bygrave, L. A. (2017) · Oslo Law Review · doi:10.18261/issn.2387-3299-2017-02-03 · Cited by 131 · see citing works
Privacy by design: delivering the promises
Hustinx, P. J. (2010) · Identity in the Information Society · doi:10.1007/s12394-010-0061-z · Cited by 87 · see citing works
Designing for Privacy and its Legal Framework
Tamò‐Larrieux, A. (2018) · Law, governance and technology series · doi:10.1007/978-3-319-98624-1 · Cited by 68 · see citing works
The European Union as Guardian of Internet Privacy
Hijmans, H. (2016) · Law, governance and technology series · doi:10.1007/978-3-319-34090-6 · Cited by 60 · see citing works
Gutwirth, S., Leenes, R. E., & Hert, P. D. (2016) · Law, governance and technology series · doi:10.1007/978-94-017-7376-8 · Cited by 43 · see citing works
On the Principle of Privacy by Design and its Limits: Technology, Ethics and the Rule of Law
Pagallo, U. (2012) · Springer eBooks · doi:10.1007/978-94-007-2903-2_16 · Cited by 33 · see citing works
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Secondary Use of Electronic Health Record: Opportunities and Challenges
Shah, S. M., & Khan, R. A. (2020) · IEEE Access · doi:10.1109/access.2020.3011099 · Cited by 158 · see citing works
- Authors
- Bincoletto, G.
- Affiliations
- University of Luxembourg (LU)
- Corresponding author
- Bincoletto, Giorgia
- ORCID
- Bincoletto, Giorgia
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2019
- Pages
- 161-181
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2956016502
- Cited by
- 9
- References
- 10
- Citations by year
- 2026: 1 · 2023: 3 · 2022: 1 · 2021: 2 · 2020: 2
- FWCI
- 7.49
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Information Systems › Thoreau and American Literature
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- privacy by design, data protection by design, electronic health records, GDPR, privacy management, data protection law, European Union law, data controllers, e-health, data subject rights
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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