BioHealth Computing schools

2-6 November 2020 - Archamps (Greater Geneva) - France 




With its as yet unfulfilled promise to revolutionize the healthcare economy and save billions of euros in the process, Artificial Intelligence (AI) and health data management in general are exploding in popularity. Indeed, the growth of the global AI health market is expected to reach US$6.6 billion by 2021.


But can AI and data-driven technologies truly live up to expectations in the field of health?


Over 5 demanding days at this exciting bioHealth Computing school, graduate students (Master & PhD) and early career professionals in science, informatics and healthcare are immersed in a challenging mix of theoretical and practical sessions on AI technology and innovation, and coached to develop business models of market-acceptable products and services using AI technologies.


Learning from Health Data is an accelerated learning programme proposed by a consortium of EIT-Health partner universities and co-organised by the Université Grenoble-Alpes and ESI-Archamps.

The school is fully in line with EU goals to deliver innovation-led solutions enabling European citizens to live longer, healthier lives. The school adheres to the 2030 Agenda for Sustainable Development of the UN, and in particular to the objectives of the UHC2030 programme whose mission is to create a movement for accelerating equitable and sustainable progress towards universal health coverage (UHC).


During the school students will :

  • follow a series of advanced courses and hands-on activities on advanced data-driven applications in health (machine learning, big data and internet of things) delivered by experts in Health Research and Development from partner universities, hospitals and industries

  • focus on unmet needs in healthcare and potential data-driven solutions

  • become familiar with experienced-based co-design, business creation, health assessment and regulatory affairs

  • develop their problem-solving and creative skills both independently and within a team

  • develop innovative ideas in multidisciplinary teams translating them into prospective business models in compliance with European health regulation

  • pitch their projects to an expert panel


The application form includes a section where candidates should provide a 50 to 200-word outline of an innovative idea or project related to health and medical data analytics. This might be expressed in terms of:

  • an unmet need in healthcare which could benefit from the development of data-driven products or services.

  • the (re)deployment of an existing technology to provide an innovative product or service for healthcare;

  • a currently unavailable but potentially marketable product or service involving data-driven technology for healthcare.

The best ideas may serve as the basis for a group project in the Business Development & Innovation component of the school.


The consortium committee is currently organising the school to run in its face-to-face format in September. However, it is possible that due to public-health measures related to the Covid-19 pandemic, this will not be possible, in which case all efforts will be made to offer an on-line version of the school.  


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