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Privacy-preserving breast cancer recurrence prediction based on homomorphic encryption and secure two party computation
Protecting patients’ privacy is one of the most important tasks when developing medical artificial intelligence models since medical data is the most sensitive personal data. To overcome this privacy protection issue, diverse privacy-preserving methods have been proposed. We proposed a novel method...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687538/ https://www.ncbi.nlm.nih.gov/pubmed/34928973 http://dx.doi.org/10.1371/journal.pone.0260681 |