Cargando…
Secure Multi-pArty Computation Grid LOgistic REgression (SMAC-GLORE)
BACKGROUND: In biomedical research, data sharing and information exchange are very important for improving quality of care, accelerating discovery, and promoting the meaningful secondary use of clinical data. A big concern in biomedical data sharing is the protection of patient privacy because inapp...
Autores principales: | Shi, Haoyi, Jiang, Chao, Dai, Wenrui, Jiang, Xiaoqian, Tang, Yuzhe, Ohno-Machado, Lucila, Wang, Shuang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959358/ https://www.ncbi.nlm.nih.gov/pubmed/27454168 http://dx.doi.org/10.1186/s12911-016-0316-1 |
Ejemplares similares
-
Grid Binary LOgistic REgression (GLORE): building shared models without sharing data
por: Wu, Yuan, et al.
Publicado: (2012) -
Grid multi-category response logistic models
por: Wu, Yuan, et al.
Publicado: (2015) -
Differentially private distributed logistic regression using private and public data
por: Ji, Zhanglong, et al.
Publicado: (2014) -
Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation
por: Kim, Miran, et al.
Publicado: (2018) -
Artis : revista cultural universitaria
Publicado: (2015)