Global healthcare fairness: We should be sharing more, not less, data

The availability of large, deidentified health datasets has enabled significant innovation in using machine learning (ML) to better understand patients and their diseases. However, questions remain regarding the true privacy of this data, patient control over their data, and how we regulate data sha...

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Detalles Bibliográficos
Autores principales: Seastedt, Kenneth P., Schwab, Patrick, O’Brien, Zach, Wakida, Edith, Herrera, Karen, Marcelo, Portia Grace F., Agha-Mir-Salim, Louis, Frigola, Xavier Borrat, Ndulue, Emily Boardman, Marcelo, Alvin, Celi, Leo Anthony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931202/
https://www.ncbi.nlm.nih.gov/pubmed/36812599
http://dx.doi.org/10.1371/journal.pdig.0000102

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931202/
https://www.ncbi.nlm.nih.gov/pubmed/36812599
http://dx.doi.org/10.1371/journal.pdig.0000102

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