
fabian.prasser@tum.de
Venia Legendi in Medical Informatics (Priv.-Doz.), TUM
Habilitation in Medical Informatics (Dr. rer. nat. habil.), TUM
Doctorate in Computer Science (Dr. rer. nat.), TUM
Degree in Computer Science (Dipl.-Inform.), TUM
Focus of Work:
Information Systems for Research, Knowledge and Information Management, Information Integration, Database Systems, Data Privacy, Data Anonymization and De-Identification
01/2013 - |
Postdoctoral Researcher, Chair of Medical Informatics, Institute of Medical Statistics and Epidemiology, TUM |
08/2012 – 10/2012 |
Research Assistant, Chair for Database Systems, Department of Computer Science, TUM |
01/2009 – 07/2012 |
Doctoral Studies, Scholarship Holder, Graduate School of Information Science in Health, TUM |
GI Gesellschaft für Informatik e.V. (German Assoc. Computer Science), Member
GMDS German Association for Medical Informatics, Biometry, and Epidemiology, Member
Selected Publications
- Prasser F, Kohlbacher O, Mansmann U, Bauer B, Kuhn KA. Data Integration for Future Medicine (DIFUTURE). Methods of Information in Medicine. 2018 Jul;57(S 01):e57-65. doi: 10.3414/ME17-02-0022
- Bild R, Kuhn KA, Prasser F. SafePub: A Truthful Data Anonymization Algorithm With Strong Privacy Guarantees. Proceedings on Privacy Enhancing Technologies. 2018 Jan 1;2018(1):67-87. doi: 10.1515/popets-2018-0004
- Prasser F, Gaupp J, Wan Z, Xia W, Vorobeychik Y, Kantarcioglu M, Kuhn KA, Malin B. An Open Source Tool for Game Theoretic Health Data De-Identification. AMIA Annual Symposium Proceedings 2017 (Vol. 2017, p.1430). American Medical Informatics Association.
- Prasser F, Kohlmayer F, Spengler H, Kuhn KA. A scalable and pragmatic method for the safe sharing of high-quality health data. IEEE Journal of Biomedical and Health Informatics 2018 Mar;22(2):611-622. doi: 10.1109/JBHI.2017.2676880.
F Prasser received the Johann Peter Süßmilch-Medal of the German Association of Medical Informatics, Biometry and Epidemiology (GMDS) for this work.
- Prasser F, Bild R, Kuhn KA. A generic method for assessing the quality of de-identified health data. Proc MIE 2016 at HEC 2016. August 2016. IOS Press. doi: 10.3233/978-1-61499-678-1-312.
F Prasser received the Peter L Reichertz Prize of the European Federation of Medical Informatics for this work.
- Prasser F, Kohlmayer F, Kuhn KA. Efficient and effective pruning strategies for health data de-identification. BMC Med Inform Decis Mak. 2016 Apr 30;16:49. doi: 10.1186/s12911-016-0287-2.
- Lautenschläger R, Kohlmayer F, Prasser F, Kuhn KA. A generic solution for web-based management of pseudonymized data. BMC Med Inform Decis Mak. 2015 Nov 30;15(1):100. doi: 10.1186/s12911-015-0222-y.
- Kohlmayer F*, Prasser F*, Kuhn KA. The cost of quality: Implementing generalization and suppression for anonymizing biomedical data with minimal information loss. J Biomed Inform. 2015 Sep 15. doi: 10.1016/j.jbi.2015.09.007.
- Prasser F*, Kohlmayer F*, Lautenschläger R, Kuhn KA. ARX - A comprehensive tool for anonymizing biomedical data. AMIA Annu Symp Proc. 2014 Nov 14;2014:984-93.
- Prasser F, Kemper A, Kuhn KA. Efficient distributed query processing for autonomous RDF databases. Proc Int Conf Extending Database Technology. 2012 Aug; 372-383. ACM. doi: 10.1145/2247596.2247640 .
(*) F Prasser and F Kohlmayer contributed equally to this work.