Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Thierry Meurers"'
Autor:
Lisa Pilgram, Thierry Meurers, Bradley Malin, Elke Schaeffner, Kai-Uwe Eckardt, Fabian Prasser
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e49445 (2024)
BackgroundSharing data from clinical studies can accelerate scientific progress, improve transparency, and increase the potential for innovation and collaboration. However, privacy concerns remain a barrier to data sharing. Certain concerns, such as
Externí odkaz:
https://doaj.org/article/8a3c485892de4264af9368126df9851d
Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients
Autor:
Carolin E. M. Koll, Sina M. Hopff, Thierry Meurers, Chin Huang Lee, Mirjam Kohls, Christoph Stellbrink, Charlotte Thibeault, Lennart Reinke, Sarah Steinbrecher, Stefan Schreiber, Lazar Mitrov, Sandra Frank, Olga Miljukov, Johanna Erber, Johannes C. Hellmuth, Jens-Peter Reese, Fridolin Steinbeis, Thomas Bahmer, Marina Hagen, Patrick Meybohm, Stefan Hansch, István Vadász, Lilian Krist, Steffi Jiru-Hillmann, Fabian Prasser, Jörg Janne Vehreschild, NAPKON Study Group
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-15 (2022)
Abstract Anonymization has the potential to foster the sharing of medical data. State-of-the-art methods use mathematical models to modify data to reduce privacy risks. However, the degree of protection must be balanced against the impact on statisti
Externí odkaz:
https://doaj.org/article/28a3080393434801b72639368e05f863
Autor:
Marco Johns, Thierry Meurers, Felix N Wirth, Anna C Haber, Armin Müller, Mehmed Halilovic, Felix Balzer, Fabian Prasser
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e42289 (2023)
BackgroundData provenance refers to the origin, processing, and movement of data. Reliable and precise knowledge about data provenance has great potential to improve reproducibility as well as quality in biomedical research and, therefore, to foster
Externí odkaz:
https://doaj.org/article/d38c30573b7747e9ad77bef8e2d626bc
Privacy-preserving data sharing infrastructures for medical research: systematization and comparison
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-13 (2021)
Abstract Background Data sharing is considered a crucial part of modern medical research. Unfortunately, despite its advantages, it often faces obstacles, especially data privacy challenges. As a result, various approaches and infrastructures have be
Externí odkaz:
https://doaj.org/article/499bd2bac2424def9c69c9a7e3bbe242
Autor:
Carolin E. M. Jakob, Florian Kohlmayer, Thierry Meurers, Jörg Janne Vehreschild, Fabian Prasser
Publikováno v:
Scientific Data, Vol 7, Iss 1, Pp 1-10 (2020)
Abstract The Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) is a European registry for studying the epidemiology and clinical course of COVID-19. To support evidence-generation at the rapid pace required in a pandemic, LEOSS follow
Externí odkaz:
https://doaj.org/article/75301dc6967641f282d7b5b64817d09f
A Flying Platform to Investigate Neuronal Correlates of Navigation in the Honey Bee (Apis mellifera)
Autor:
Benjamin H. Paffhausen, Julian Petrasch, Benjamin Wild, Thierry Meurers, Tobias Schülke, Johannes Polster, Inga Fuchs, Helmut Drexler, Oleksandra Kuriatnyk, Randolf Menzel, Tim Landgraf
Publikováno v:
Frontiers in Behavioral Neuroscience, Vol 15 (2021)
Navigating animals combine multiple perceptual faculties, learn during exploration, retrieve multi-facetted memory contents, and exhibit goal-directedness as an expression of their current needs and motivations. Navigation in insects has been linked
Externí odkaz:
https://doaj.org/article/6065367dd3c542a8bf6b4167a08a1190
Autor:
Marco Johns, Thierry Meurers, Felix N Wirth, Anna C Haber, Armin Müller, Mehmed Halilovic, Felix Balzer, Fabian Prasser
BACKGROUND Data provenance refers to the origin, processing, and movement of data. Reliable and precise knowledge about data provenance has great potential to improve reproducibility as well as quality in biomedical research and, therefore, to foster
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c34d94c9cab9a302395d9933bcf623f1
https://doi.org/10.2196/preprints.42289
https://doi.org/10.2196/preprints.42289
Publikováno v:
Studies in health technology and informatics. 294
In this study, we propose a unified evaluation framework for systematically assessing the utility-privacy trade-off of synthetic data generation (SDG) models. These SDG models are adapted to deal with longitudinal or tabular data stemming from electr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::f1464eaf9a9ba9edaa994292970a94dd
https://pubmed.ncbi.nlm.nih.gov/35612040
https://pubmed.ncbi.nlm.nih.gov/35612040
In this study, we propose a unified evaluation framework for systematically assessing the utility-privacy trade-off of synthetic data generation (SDG) models. These SDG models are adapted to deal with longitudinal or tabular data stemming from electr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5eb71aac4e465e85fe7922496071411
https://doi.org/10.3233/shti220420
https://doi.org/10.3233/shti220420
Publikováno v:
Journal of Biomedical Informatics. 137:104257
Effective and efficient privacy risk management (PRM) is a necessary condition to support digitalization in health care and secondary use of patient data in research. To reduce privacy risks, current PRM frameworks are rooted in an approach trying to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31423bb5b98276c906e14fdaafd94f14
https://doi.org/10.1016/j.jbi.2022.104257
https://doi.org/10.1016/j.jbi.2022.104257