User: Guest  Login
Document type:
Review 
Author(s):
Kaissis, Georgios A.; Makowski, Marcus R.; Ruckert, Daniel; Braren, Rickmer F. 
Title:
Secure, privacy-preserving and federated machine learning in medical imaging 
Abstract:
The broad application of artificial intelligence techniques in medicine is currently hindered by limited dataset availability for algorithm training and validation, due to the absence of standardized electronic medical records, and strict legal and ethical requirements to protect patient privacy. In medical imaging, harmonized data exchange formats such as Digital Imaging and Communication in Medicine and electronic data storage are the standard, partially addressing the first issue, but the req...    »
 
Journal title abbreviation:
Nat. Mach. Intell. 
Year:
2020 
Journal volume:
Journal issue:
Pages contribution:
305-311 
TUM Institution:
Institut für Diagnostische und Interventionelle Radiologie; Institut für Medizinische Statistik und Epidemiologie