A guest post by Gorana Nikolic from KU Leuven With increased usage of AI in international projects that have large and versatile consortium members, there is a strong need to […]
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MIDAS: The importance of data for health policy
Guest post by Paul Carlin of Open University / South Eastern Health and Social Care Trust At times, when participating in healthcare research, one cannot help but feel slightly divorced […]
Release Data from Silos…, but Triumph in the Paper War First
A guest post by Juha Pajula from VTT The traditional way to define research projects in health (and other) domains is first to define challenge to study and how to […]
A MIDAS contribution to the global COVID-19 monitoring strategy
Guest post by Joao Pita Costa from (Quintelligence) As the world starts to realise the potential global impact of the Coronavirus (COVID-19) which has just been declared a Pandemic by the […]
MIDAS: Big Data for Health Policy Symposium, 20-21 January 2020
Guest post by Jonathan Wallace from Ulster University Ulster University’s Magee campus, in Derry/Londonderry, hosted the European Union funded ‘Big Data for Health Policy Symposium’ on the 20th and 21st […]
How to manage privacy in a database used for biomedical research purposes under the GDPR
Guest post by Iker Ezkerra Elizalde from BIOEF Our personal data are highly valuable, especially if we consider health-related data. This is because they contain sensitive private information of which we […]
“UPCOMING” – BIG DATA FOR HEALTH POLICY SYMPOSIUM – Derry Jan 20-21, 2020
The MIDAS Consortium is hosting BIG DATA FOR HEALTH POLICY SYMPOSIUM MIDAS project to Magee on 20th -21st January in Derry (Northern Ireland). This project is due to finish in […]
“Twas The Big Data Revolution Before Christmas…”
A guest post by Emily Orchard & Dale Weston from Public Health England Whilst typically this time of year can be considered, for some, a time for relaxing and winding down, for one person […]
How do we ensure AI is used in an ethical way?
A guest post by Scott Fischaber from Analytics Engines Analytics Engines is supporting MIDAS in its aim to map, acquire, manage, model, process, and exploit existing heterogeneous healthcare data and […]
Opportunities in MIDAS Platform Reuse
Guest post by Jarmo Pääkkönen from Centre for Health and Technology, University of Oulu The MIDAS platform has been developed for policy making and data analytics from various health-related data […]