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First Experiences Implementing Predictive Analytics Tools in a Clinical Routine Setting

Authors:
Oliver Klar
Raluca Dees
Rasim Atakan Poyraz
Gerd Schneider
Oliver Heinze

Keywords: clinical artificial intelligence; artificial intelligence in healthcare; monitoring networked medical devices

Abstract:
The rise of Artificial Intelligence(AI) is ubiquitous. In healthcare it is seen as a key technology supporting clinicians in their daily routine. The PART research project (Predictive Analytics of Robustness Testing) aims to develop an AI driven system which has the focus on networked device monitoring, profitability analysis and predictive maintenance in a clinical environemt. However before thinking about sophisticated AI algorithms at Heidelberg University Hospital we experienced a variety of difficulties according to medical device data acquisition from various manufactures and data protection which have to be solved first. This paper focuses on those difficilitues in a very early stage of the project and makes suggestions for suitable solutions.

Pages: 114 to 115

Copyright: Copyright (c) IARIA, 2019

Publication date: February 24, 2019

Published in: conference

ISSN: 2308-4359

ISBN: 978-1-61208-688-0

Location: Athens, Greece

Dates: from February 24, 2019 to February 28, 2019