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Health-RI Conference 2020: Towards Data Driven Health

Jan 30 2020

Luiz Bonino and Erik Schultes will attend the FAIRstifal workshop “Let’s GO FAIR” that is part of the Health-RI Conference 2020.

Learn more about this conference

How is data helping us to remain healthy?
How can we learn from today’s patients so that tomorrow’s patients get better treatment?
Leading experts will address these questions, the enablers and challenges on the road to
data-driven health. At the Health-RI conference 2020 on January 30th in the Jaarbeurs
Utrecht.

We all want to stay healthy for as long as possible. When we do face health problems, we
look for the best treatment – the right treatment at the right time, tailormade. To make that
possible, data is essential. It’s a matter of continuous learning and improvement – evidence
based with the help of enormous amounts of data in different formats and from various
sources. We’re already learning how to combine that data in clever ways, tailoring it to
specific situations and applying it to our everyday health choices.

Key-note speaker is Dr. Eimear E. Kenny, from the Icahn School of Medicine at Mount Sinai
in New York on personalized medicine and the power of electronic health records.

Hosting the FAIRstival
This year, the health-RI conference is hosting the FAIRstival, an event where datamanagers
working in health care and health research can exchange experiences with implementation
of FAIR data principles and the Personal Health Train.

Call for abstracts: share your expertise, experience and ideas
The Health-RI 2020 conference will host a poster & demonstration session and the
opportunity for short plenary pitches. Please check the abstract submission guidelines.

Health-RI 2020: Towards Data Driven Health
Check the Health-RI conference and registration
Visit the Health-RI webportal.

About Health-RI
Health-RI is the Dutch national initiative to facilitate and stimulate an integrated health data infrastructure accessible for researchers, citizens and care providers. It will enable optimal use of health data, samples and images, a learning healthcare system and accelerate personalized health.