Artificial Intelligence to boost hospital care to the future
Healthcare systems lack flexible AI solutions that allow hospitals to improve efficiency and quality of patient care. Current solutions provide limited scalability and are confined to isolated applications. Scalable models that address data sharing, integration, privacy, and ethics are needed to ensure better adoption of AI in healthcare.
Five European hospitals will test these pilots with their users to prove the scalability of the SHCP Engine
Helsinki University
Hospital (Finland)
SJD Barcelona Children's
Hospital (Spain)
Bambino Gesù
Pediatric Hospital (Italy)
Oulu University
Hospital (Finland)
Padua University
Hospital (Italy)
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Implementing AI developments in healthcare. What we have learned
AICCELERATE has been an ambitious project to implement an open AI-based solution in 5 hospital settings, focused on 3 different use cases. After three years, we have learned a lot, and we want to share those lessons learned with you.
AICCELERATE project’s newsletter released its fifth issue this month with some interesting news and upcoming events. Didn’t receive it? You can read it here. If you don’t want to miss a thing, don’t forget to subscribe here!
Webinar on AI-driven research projects for Hospitals. How to face them?
How tough is it to deal with all the practicalities of data sharing for AI-driven research? Navigating the landscape of data sharing in AI-driven research is similar to traversing a complex labyrinth fraught with challenges and obstacles. We are living a paradigm switch from a traditional approach to clinical and scientific research to a system that calls for interdisciplinarity from the beginning. Today’s research landscape demands collaboration from inception. Working together with ethical committees, data protection officers, and legal experts...
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