SoftwareX, 2023 As open science principles continue to gain traction, striking a balance between patient privacy and data accessibility has become more crucial in medical research than ever before.
Manfred Schedlowski +2 more
exaly +3 more sources
The Advanced Confidentiality Engine as a Scalable Tool for the Pseudonymization of Biomedical Data in Translational Settings: Development and Usability Study [PDF]
Journal of Medical Internet ResearchBackgroundPseudonymization refers to a process in which data that directly identify individuals, such as names and addresses, are stored separately from data needed for scientific purposes.
Armin Müller +5 more
doaj +2 more sources
Pseudonymization tools for medical research: a systematic review [PDF]
BMC Medical Informatics and Decision MakingBackground Pseudonymization is an important technique for the secure and compliant use of medical data in research. At its core, pseudonymization is a process in which directly identifying information is separated from medical research data.
Hammam Abu Attieh +3 more
doaj +2 more sources
Deep learning enabled pseudonymization for preserving data privacy of financial identifiers in public documents in India [PDF]
Scientific ReportsThe increasing digitization and transmission of government-issued electronic documents have intensified the need to protect the ’Handwritten signatures’-recognized as ’critical biometric identifiers’ from identity-related data breaches.
R. Roopalakshmi +2 more
doaj +2 more sources
Extraction and processing of intensive care chart data from a patient data management system [PDF]
Frontiers in Digital HealthBackgroundRoutine clinical data captured in Patient Data Management Systems (PDMS) in intensive care and perioperative settings are an invaluable resource for clinical research.
Nikolas B. Schrader +6 more
doaj +2 more sources
Possibilities for secondary data use of electronic health records with WiseSpace de-identification [PDF]
Frontiers in MedicineIntroductionThe secondary use of Electronic Health Records (EHRs) holds significant potential for advancing research, public health, and innovation. However, data sharing is often limited by privacy regulations, requirements, and technical complexity ...
Olga Vovk +3 more
doaj +2 more sources
Pseudonymization risk analysis in distributed systems
Journal of Internet Services and Applications, 2019 In an era of big data, online services are becoming increasingly data-centric; they collect, process, analyze and anonymously disclose growing amounts of personal data in the form of pseudonymized data sets. It is crucial that such systems are engineered
Paul Grace, Grace Paul, Surridge Mike
exaly +3 more sources
End-to-end pseudonymization of fine-tuned clinical BERT models [PDF]
BMC Medical Informatics and Decision MakingMany state-of-the-art results in natural language processing (NLP) rely on large pre-trained language models (PLMs). These models consist of large amounts of parameters that are tuned using vast amounts of training data. These factors cause the models to
Thomas Vakili +2 more
doaj +2 more sources
A Scalable Pseudonymization Tool for Rapid Deployment in Large Biomedical Research Networks: Development and Evaluation Study [PDF]
JMIR Medical InformaticsBackgroundThe SARS-CoV-2 pandemic has demonstrated once again that rapid collaborative research is essential for the future of biomedicine. Large research networks are needed to collect, share, and reuse data and biosamples to generate collaborative ...
Hammam Abu Attieh +6 more
doaj +2 more sources
A comprehensive dataset of customer behavior in Latin American Fintech: 12-month transactional and demographic data for churn analysisMendeley Data [PDF]
Data in BriefThis article introduces COFINFAD (Colombian Fintech Financial Analytics Dataset), a single-company 12-month dataset containing comprehensive behavioral information from 48,723 customers (representing the complete active customer base) of a Colombian ...
Luis Eduardo Muñoz-Guerrero, Ph.D. +2 more
doaj +2 more sources