[HTML][HTML] Federated machine learning, privacy-enhancing technologies, and data protection laws in medical research: scoping review
A Brauneck, L Schmalhorst… - Journal of Medical …, 2023 - jmir.org
Background The collection, storage, and analysis of large data sets are relevant in many
sectors. Especially in the medical field, the processing of patient data promises great …
sectors. Especially in the medical field, the processing of patient data promises great …
[HTML][HTML] Privacy-aware multi-institutional time-to-event studies
Clinical time-to-event studies are dependent on large sample sizes, often not available at a
single institution. However, this is countered by the fact that, particularly in the medical field …
single institution. However, this is countered by the fact that, particularly in the medical field …
Collection, usage and privacy of mobility data in the enterprise and public administrations
A Kapp - arXiv preprint arXiv:2407.03732, 2024 - arxiv.org
Human mobility data is a crucial resource for urban mobility management, but it does not
come without personal reference. The implementation of security measures such as …
come without personal reference. The implementation of security measures such as …
KI-basiertes akustisches Monitoring: Herausforderungen und Lösungsansätze für datengetriebene Innovationen auf Basis audiovisueller Analyse
P Aichroth, J Liebetrau - … und Anwendung von Künstlicher Intelligenz im …, 2023 - Springer
KI-basierte audiovisuelle Analyse kann datengetriebene Produkt-, Prozess-und auch
Geschäftsmodellinnovationen in verschiedenen Anwendungsbereichen befördern …
Geschäftsmodellinnovationen in verschiedenen Anwendungsbereichen befördern …
[PDF][PDF] Privacy-aware multi-institutional time-to-event studies. PLOS Digit Health 1 (9): e0000101
J Späth, J Matschinske, FK Kamanu, SA Murphy… - 2022 - featurecloud.eu
Clinical time-to-event studies are dependent on large sample sizes, often not available at a
single institution. However, this is countered by the fact that, particularly in the medical field …
single institution. However, this is countered by the fact that, particularly in the medical field …
[PDF][PDF] Herausforderungen Privatsphäre erhaltender KI
M Krämer - 14th SPRING graduate workshop, 2024 - fg-sidar.gi.de
Ziel Privatsphäre erhaltender maschineller Lernalgorithmen ist es, Vorhersagemodelle
mittels verschiedener Datensilos zu trainieren, ohne die Rohdaten an einer zentralen Stelle …
mittels verschiedener Datensilos zu trainieren, ohne die Rohdaten an einer zentralen Stelle …