Under CopyrightZiegler, WolfgangWolfgangZieglerIhle, MatthiasMatthiasIhleClaus, SteffenSteffenClausSenger, PhilippPhilippSengerMohebbi, PooyaPooyaMohebbiKhan, ZakirZakirKhanFluck, JulianeJulianeFluckGriebel, LenaLenaGriebelSedlmayr, MartinMartinSedlmayrBerger, FlorianFlorianBergerLaufer, JulianJulianLauferChatziastros, AstrosAstrosChatziastrosDrepper, JohannesJohannesDrepper2022-03-1212.11.20132013https://publica.fraunhofer.de/handle/publica/38119310.24406/publica-fhg-381193Patient data describing operations and results of treatment in clinics is stored in clinical information systems as part of the clinical process. Since these documents are unstructured free-texts stored as scanned documents or as documents prepared with a word processing system there was no automated way to find patterns in these documents that indicate significant accumulations of e.g., treatments and side effects. As a result, valuable information hidden in this huge amount of data spread across clinics is just neglected. A solution is the automated processing of unstructured data from different sources with advanced text mining technology. However, processing a large amount of scanned documents in general exceeds the computational power available in clinics. Using Cloud resources on a p ay per use basis is a cost-efficient alternative to accomplish this task. We describe the approach of the cloud4health project, its framework for processing anonymized patient data, and its data protection and security developments to turn a Cloud into a trusted Cloud where the data may be processed in compliance with legal requirements.encloud computingpatient medical datadata protectionsecuritytrust003005006518conference paper