Secure tumor classification by shallow neural network using homomorphic encryption

BACKGROUND: Disclosure of patients’ genetic information in the process of applying machine learning techniques for tumor classification hinders the privacy of personal information. Homomorphic Encryption (HE), which supports operations between encrypted data, can be used as one of the tools to perfo...

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Detalles Bibliográficos
Autores principales: Hong, Seungwan, Park, Jai Hyun, Cho, Wonhee, Choe, Hyeongmin, Cheon, Jung Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994372/
https://www.ncbi.nlm.nih.gov/pubmed/35395714
http://dx.doi.org/10.1186/s12864-022-08469-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994372/
https://www.ncbi.nlm.nih.gov/pubmed/35395714
http://dx.doi.org/10.1186/s12864-022-08469-w

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