Results 81 to 90 of about 21,719,510 (360)
Reconstruction Attacks on Aggressive Relaxations of Differential Privacy [PDF]
Differential privacy is a widely accepted formal privacy definition that allows aggregate information about a dataset to be released while controlling privacy leakage for individuals whose records appear in the data. Due to the unavoidable tension between privacy and utility, there have been many works trying to relax the requirements of differential ...
arxiv
Cancer stem cells are associated with aggressive disease, but a deep characterization of such markers is lacking in endometrial cancer. This study uses imaging mass cytometry to explore putative cancer stem cell markers in endometrial tumors and corresponding organoid models.
Hilde E. Lien+7 more
wiley +1 more source
Big Data and the Ethical Implications of Data Privacy in Higher Education Research
Despite the claimed worth and huge interest regarding the increasing volumes of complex data sets and the rewarding promise to improve research, there is, however, a growing concern regarding data privacy that affects both qualitative and quantitative ...
Diana Florea, S. Florea
semanticscholar +1 more source
Privacy, Data and the Individual
Personal ...
Center For The Governance Of Change+1 more
openaire +3 more sources
Privacy and Data-Based Research [PDF]
What can we, as users of microdata, formally guarantee to the individuals (or firms) in our dataset, regarding their privacy? We retell a few stories, well-known in data-privacy circles, of failed anonymization attempts in publicly released datasets.
Katrina Ligett+3 more
openaire +7 more sources
The roles and applications of extracellular vesicles in cancer
Extracellular vesicles (EVs) are minute versions of cells limited by a lipid bilayer containing cytoplasm from the cell that releases them, but without a nucleus and thus unable to self‐reproduce. EVs contain multiple molecules (proteins, lipids, glycans, and nucleic acids) they can induce complex responses in cells.
Clotilde Théry, Daniel Louvard
wiley +1 more source
Big Data Privacy in Biomedical Research
Biomedical research often involves studying patient data that contain personal information. Inappropriate use of these data might lead to leakage of sensitive information, which can put patient privacy at risk.
Shuang Wang+7 more
semanticscholar +1 more source
Big Data Privacy: Challenges to Privacy Principles and Models [PDF]
Abstract This paper explores the challenges raised by big data in privacy-preserving data management. First, we examine the conflicts raised by big data with respect to preexisting concepts of private data management, such as consent, purpose limitation, transparency and individual rights of access, rectification and erasure.
Soria-Comas, Jordi+1 more
openaire +2 more sources
Germline variants in CDKN2A wild‐type melanoma prone families
Among melanoma‐prone families, wild‐type for CDKN2A and CDK4, some have pathogenic variants in genes not usually linked to melanoma. Furthermore, rare XP‐related variants and variants in MC1R are enriched in such families. Germline pathogenic variants in CDKN2A are well established as an underlying cause of familial malignant melanoma. While pathogenic
Gjertrud T. Iversen+5 more
wiley +1 more source
A Unified Framework for Quantifying Privacy Risk in Synthetic Data [PDF]
Synthetic data is often presented as a method for sharing sensitive information in a privacy-preserving manner by reproducing the global statistical properties of the original data without disclosing sensitive information about any individual. In practice, as with other anonymization methods, privacy risks cannot be entirely eliminated.
arxiv