Results 41 to 50 of about 24,103,638 (294)
Algorithms to anonymize structured medical and healthcare data: A systematic review
Introduction: With many anonymization algorithms developed for structured medical health data (SMHD) in the last decade, our systematic review provides a comprehensive bird’s eye view of algorithms for SMHD anonymization.Methods: This systematic review ...
Ali Sepas +6 more
doaj +1 more source
Computer vision has become indispensable in various applications, including autonomous driving, medical imaging, security and surveillance, robotics, and pattern recognition.
Jun Ha Lee, Sujeong You
semanticscholar +1 more source
Utility-preserving anonymization for health data publishing
Background Publishing raw electronic health records (EHRs) may be considered as a breach of the privacy of individuals because they usually contain sensitive information.
Hyukki Lee +3 more
doaj +1 more source
Data anonymization is an essential prerequisite that enables data sharing in a privacy-preserving manner. However, anonymization affects the quality of the data and thus might affect the performance of later conducted data analysis.
Roland Stenger +4 more
doaj +1 more source
Improving MapReduce privacy by implementing multi-dimensional sensitivity-based anonymization
Big data is predominantly associated with data retrieval, storage, and analytics. Data analytics is prone to privacy violations and data disclosures, which can be partly attributed to the multi-user characteristics of big data environments.
Mohammed Al-Zobbi +2 more
doaj +1 more source
Anonymizing Temporal Data [PDF]
Temporal data are time-critical in that the snapshot at each timestamp must be made available to researchers in a timely fashion. However, due to the limited data, each snapshot likely has a skewed distribution on sensitive values, which renders classical anonymization methods not possible.
Ke Wang +3 more
openaire +1 more source
Implementation of a big data anonymization system based on Spark
Group based anonymization is a classical data anonymization framework,which achieves the effect of privacy protection by constructing groups of anonymized data records ensuring that records in the same group cannot be distinguished with each other.The ...
Chaoyi BIAN, Shaomin ZHU, Tao ZHOU
doaj +2 more sources
ANONYMIZATION OF PERSONAL MEDICAL DATA BASED ON ARTIFICIAL INTELLIGENCE [PDF]
The widespread digitalization of healthcare has led to the accumulation of substantial volumes of personal medical data, creating new opportunities for enhancing the quality of medical care, supporting informed clinical decision-making, and ...
Ramiz Shikhaliyev
doaj +1 more source
Utility-driven assessment of anonymized data via clustering
In this study, clustering is conceived as an auxiliary tool to identify groups of special interest. This approach was applied to a real dataset concerning an entire Portuguese cohort of higher education Law students.
Maria Eugénia Ferrão +2 more
doaj +1 more source
The PI3Kδ inhibitor roginolisib (IOA‐244) preserves T‐cell function and activity
Identification of novel PI3K inhibitors with limited immune‐related adverse effects is highly sought after. We found that roginolisib and idelalisib inhibit chronic lymphocytic leukemia (CLL) cells and Treg suppressive functions to similar extents, but roginolisib affects cytotoxic T‐cell function and promotion of pro‐inflammatory T helper subsets to a
Elise Solli +7 more
wiley +1 more source

