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Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform.
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Swansea University
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9644981/ http://dx.doi.org/10.23889/ijpds.v7i3.2023 |
| _version_ | 1784826866086969344 |
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| author | Farrow, Luke Wilde, Katie Dymiter, Jaroslaw Boyle, Moragh Weir, Alexander Blackwood, James Mayor, Charlie Harrison, David Anderson, Lesley |
| author_facet | Farrow, Luke Wilde, Katie Dymiter, Jaroslaw Boyle, Moragh Weir, Alexander Blackwood, James Mayor, Charlie Harrison, David Anderson, Lesley |
| author_sort | Farrow, Luke |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-9644981 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Swansea University |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-96449812022-11-18 Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform. Farrow, Luke Wilde, Katie Dymiter, Jaroslaw Boyle, Moragh Weir, Alexander Blackwood, James Mayor, Charlie Harrison, David Anderson, Lesley Int J Popul Data Sci Article Swansea University 2022-08-25 /pmc/articles/PMC9644981/ http://dx.doi.org/10.23889/ijpds.v7i3.2023 Text en https://creativecommons.org/licenses/by/4.0/This work is licenced under a Creative Commons Attribution 4.0 International License. |
| spellingShingle | Article Farrow, Luke Wilde, Katie Dymiter, Jaroslaw Boyle, Moragh Weir, Alexander Blackwood, James Mayor, Charlie Harrison, David Anderson, Lesley Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform. |
| title | Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform. |
| title_full | Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform. |
| title_fullStr | Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform. |
| title_full_unstemmed | Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform. |
| title_short | Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform. |
| title_sort | use of “hidden in plain sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: results from the icaird safe haven artificial intelligence platform. |
| topic | Article |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9644981/ http://dx.doi.org/10.23889/ijpds.v7i3.2023 |
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