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TALKS: Self-Service Data Science @HEALTHINF 2020

posted Feb 29, 2020, 6:50 AM by Marco Spruit
The 13th International Health Informatics (HealthInf 2020) conference took place in Valetta, and started – interestingly – with a 90 minutes long panel. The topic was on the undeniable gap between research and development, and, even worse yet, between development and operation: this is the "long mile" between research and medical practice that separates our best solutions from also becoming best practices and from achieving lasting impact at the point-of-care, and on the patients' illness trajectories and outcome. “Has the time come to move from the technical and embrace a more socio-technical, holistic approach?”

Of the keynote speakers in the panel, Helena Canhão introduced her Patient innovation project which focuses on patient entrepreneurship and has already collected 1000 innovations, however, many of them have not yet passed regulatory procedures to ensure patient safety. Roy Huddle specialises in visual analytics which helps explain how AI works (XAI) and can be considered a key tool to develop Trust in combination with using open data, open AI models, and external validation. Silvana Quaglini highlighted the role of the attitude of the medical professionals and the need for educating next generations of healthcare professionals to increase understanding and thus Trust in decision support systems and AI technologies. Finally, Federico Cabitza explained the gap between research and practice in more depth, citing some interesting works as well, with titles such as "The Last Mile: Where Artificial Intelligence Meets Reality", "Artificial Intelligence in Health Care: Will the Value Match the Hype?", and "The proof of the pudding: in praise of a culture of real-world validation for medical artificial intelligence". Unfortunately, at least within the regular programme, there were hardly any actual presentations on this key topic, once again illustrating the urgency of this viewpoint...

On a personal note, I presented our poster on Self-Service Data Science for Healthcare Professionals, which addresses this gap between research and practice by supporting the physicians in doing the data analysis themselves, as much as possible, capitalising upon the idea of "Trust Through Empowerment".