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Experience made using public cloud infrastructure to analyse clinical patient data

: Ziegler, Wolfgang; Ihle, Matthias; Claus, Steffen; Senger, Philipp; Mohebbi, Pooya; Khan, Zakir; Fluck, Juliane; Griebel, Lena; Sedlmayr, Martin; Berger, Florian; Laufer, Julian; Chatziastros, Astros; Drepper, Johannes

Fulltext urn:nbn:de:0011-n-2664843 (285 KByte PDF)
MD5 Fingerprint: d0293bbf12523a8177a9abde1d6c55a5
Created on: 12.11.2013

Cunningham, P. ; International Information Management Corp. - IIMC-, Dublin:
eChallenges 2013. Proceedings : 09.10.-11.10.2013, Dublin, Irland
Dublin: IIMC, 2013
ISBN: 978-1-905824-40-3
13 pp.
eChallenges Conference <2013, Dublin>
Bundesministerium für Wirtschaft und Technologie BMWi
Trusted Cloud; cloud4helth
Conference Paper, Electronic Publication
Fraunhofer SCAI ()
cloud computing; patient medical data; data protection; security; trust

Patient 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.