Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Fabian Praßer"'
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 19, Iss 1, Pp 1-8 (2024)
Abstract Background Globally, researchers are working on projects aiming to enhance the availability of data for rare disease research. While data sharing remains critical, developing suitable methods is challenging due to the specific sensitivity an
Externí odkaz:
https://doaj.org/article/fa589ac1d392488da873d187ea3f33f4
Autor:
Lisa Kühnel, Julian Schneider, Ines Perrar, Tim Adams, Sobhan Moazemi, Fabian Prasser, Ute Nöthlings, Holger Fröhlich, Juliane Fluck
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Access to individual-level health data is essential for gaining new insights and advancing science. In particular, modern methods based on artificial intelligence rely on the availability of and access to large datasets. In the health sector
Externí odkaz:
https://doaj.org/article/b307ab374bf44a03942d1eb50b9554d3
Autor:
Michele Zoch, Christian Gierschner, Anne-Katrin Andreeff, Elisa Henke, Martin Sedlmayr, Gabriele Müller, Jenny Tippmann, Helge Hebestreit, Daniela Choukair, Georg F. Hoffmann, Fleur Fritz-Kebede, Nicole Toepfner, Reinhard Berner, Stephanie Biergans, Raphael Verbücheln, Jannik Schaaf, Julia Fleck, Felix Nikolaus Wirth, Josef Schepers, Fabian Prasser
Publikováno v:
Digital Health, Vol 10 (2024)
Objective Unlocking the potential of routine medical data for clinical research requires the analysis of data from multiple healthcare institutions. However, according to German data protection regulations, data can often not leave the individual ins
Externí odkaz:
https://doaj.org/article/6640c4e05bff445292a3e4d25a2ab079
Autor:
Chiara Dellacasa, Maurizio Ortali, Elisa Rossi, Hammam Abu Attieh, Thomas Osmo, Miroslav Puskaric, Eugenia Rinaldi, Fabian Prasser, Caroline Stellmach, Salvatore Cataudella, Bhaskar Agarwal, Juan Mata Naranjo, Gabriella Scipione
Publikováno v:
Digital Health, Vol 10 (2024)
Background The ORCHESTRA project, funded by the European Commission, aims to create a pan-European cohort built on existing and new large-scale population cohorts to help rapidly advance the knowledge related to the prevention of the SARS-CoV-2 infec
Externí odkaz:
https://doaj.org/article/b3fa3cfa00c34936a866a661969c0c86
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
IntroductionThe open-source software offered by the Observational Health Data Science and Informatics (OHDSI) collective, including the OMOP-CDM, serves as a major backbone for many real-world evidence networks and distributed health data analytics p
Externí odkaz:
https://doaj.org/article/84d31d04ef9d41358efd564bb236a98d
Autor:
Hammam Abu Attieh, Diogo Telmo Neves, Mariana Guedes, Massimo Mirandola, Chiara Dellacasa, Elisa Rossi, Fabian Prasser
Publikováno v:
JMIR Medical Informatics, Vol 12, Pp e49646-e49646 (2024)
Abstract BackgroundThe 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 coll
Externí odkaz:
https://doaj.org/article/e5f365df795f4645b3272d994d61259d
Development of a Trusted Third Party at a Large University Hospital: Design and Implementation Study
Autor:
Eric Wündisch, Peter Hufnagl, Peter Brunecker, Sophie Meier zu Ummeln, Sarah Träger, Marcus Kopp, Fabian Prasser, Joachim Weber
Publikováno v:
JMIR Medical Informatics, Vol 12, Pp e53075-e53075 (2024)
Abstract BackgroundPseudonymization has become a best practice to securely manage the identities of patients and study participants in medical research projects and data sharing initiatives. This method offers the advantage of not requiring the dire
Externí odkaz:
https://doaj.org/article/194ae887c5d344289cd34a42ce72f875
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
Autor:
Petr Holub, Heimo Müller, Tomáš Bíl, Luca Pireddu, Markus Plass, Fabian Prasser, Irene Schlünder, Kurt Zatloukal, Rudolf Nenutil, Tomáš Brázdil
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-15 (2023)
Abstract Access to large volumes of so-called whole-slide images—high-resolution scans of complete pathological slides—has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education
Externí odkaz:
https://doaj.org/article/9c9ee166c04045f5a114176b5087ddd5
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