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Session 6 | Looking forwards: Operational pathway to AI implementation

Session 6 speakers final
 
With the support of COMFORTage.
 
Artificial Intelligence (AI) is increasingly seen as being able to revolutionise healthcare through early detection, enhanced diagnosis, personalised treatment, and predictive power. In this session, we will explore one of the many challenges to installing AI in the landscape : the need to access and integrate a wide variety of quality data from areas such as biomarkers, genomics, images, wearables, and PREMs and PROMs, create structural collaboration between Healthcare organisations and Industry and create the appropriate environment to develop, test and validate algorithms.

🕐 Session Programme

► Session introduction

Andrea Jester, NSBproject s.r.l., Italy


► Is AI the magic tool to normalise data ?

Benny Van Bruwaene, BT computing, Belgium

AI needs a large volume of quality and structured data to produce meaningful results. But today a lot of data remain unfit to communicate with machines due to their lack of structuration and codification. Can AI also be a solution to solve this essential bottleneck? If yes, for which kind of data? Which human interaction remains necessary? What are the conditions needed to make use of those tools?


► How to be sure AI delivers its promise?

Dr. Tal Patalon, Head of KSM, Maccabi Healthcare Services Research and Innovation Center, Israel

Even when health data is available and fits the purpose, creating the appropriate environment to develop, test and successfully deploy AI solutions, is still complex and challenging. The transformative potential of AI in the healthcare industry is on the brink of realization - yet there is still a long way to go in bridging the gap between innovation and real world implementationTogether with genetic data being included in EHR, a world of possibilities will emerge, requiring us to find solutions that allow the use of advanced technologies based on information from real world data.


► The TEF-Health: a new ecosystem for AI implementation

Prof. Petra Ritter, Charité, TEF-Health Coordinator, Germany

The TEF program is a pioneering project that aims to set up a network dedicated to testing innovative solutions in AI in the health sector. For companies specializing in AI and MedTech, TEF-Health will offer them easy access to medical data as well as to leading clinical, legal and technological expertise in order to validate their technological solutions and accelerate and increase their adoption on the market.


► Co-creating innovative AI in a European Project around dementia

Aris Tsitiridis, UBITECH, Greece

Where to start when an AI focused innovative project has to integrate retrospective and prospective data from multiple European pilot sites and develop AI enabled processes in a limited timeframe? An IT vision of the challenges in deploying AI at scale for a specific purpose in a cross border environement.


► Moderated debate


All speakers will be fully confirmed shortly, stay tuned!

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