This new bioHealth Computing school addresses the complex challenge of reinventing European healthcare systems in the light of Artificial Intelligence (AI). Focusing on healthy living and active ageing, the school uses a needs-led approach founded on experience-based co-design methodology.
Participants will learn how to optimize R&D efficiency in innovative A.I. for health projects and also how to bridge the gap between the proof of efficacy required to pass regulatory scrutiny and the statistical demonstration of likely effectiveness needed to satisfy health technology assessment bodies.
COURSE DELIVERY & LEARNING OUTCOMES
School Coordinator : Philippe Sabatier (Université Grenoble Alpes)
A challenging mix of theoretical and practical modules in A.I. technology and innovation will inspire participants to develop business models of market-acceptable products and services using A.I. technologies.
The team with the best idea/business plan will be offered the opportunity develop their project with the KTH – EIT Health incubator.
COMPONENT 1
Learning outcomes: By the end of the School, participants will have learned to :
- Understand what constitutes A.I. in terms of objectives, concepts and functions, and how A.I. brings capabilities beyond conventional technology,
- Implement A.I. techniques, such as Search algorithms, Bayesian networks, Machine and Reinforcement learning for problem solving,
- Understand the limits of current A.I. techniques,
- Categorize an A.I. problem based on its characteristics and constraints.
COMPONENT 2
Learning outcomes: By the end of the School, participants will have learned to :
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- Assess the needs (clinical and market) of developing a new A.I. based app and define the outline of the development plan of this app.
- Review and evaluate medical innovations; Manage usability studies, clinical investigations and post-market follow-up studies,
- Appreciate the « confidentiality » of information, maintain the protection of industrial property, find the necessary regulations for the development of a new technologies,
- Analyse complex health, wellbeing and ageing conditions; Identify short- and long-term consequences of plans and decisions; Adapt professional practices, moving towards a sustainable society.
COMPONENT 3
Learning outcomes : By the end of the School, participants will have learned to :
- Think beyond boundaries and systematically explore and design/invent/implement a new idea, system, component or process which meets emergent needs in healthcare and wellbeing
- Develop an understanding of patient/citizen needs,
- Identify, formulate and solve engineering problems in the healthcare domain, and translate innovations into feasible business solutions within realistic constraints (economic, environmental, social, political, ethical, safety …),
- Decision-making and leadership, based on a holistic understanding of the contributions of Higher Education, research and business to value creation, in limited sized teams.
SELECTION
Pre-ranking of applicants is based on academic background in order to ensure a cross-disciplinary student body.
Final selection is based on the applicants CV, stated motivation and relevance of the proposed innovation project. Criteria will focus on the capacity for calculated risk, focus on community, open and critical thinking, initiative with follow-through.
Successful applicants will be informed by (date to be announced).
REGISTRATION FEES
Registration fee: €600
ESI has pre-booked single rooms at the Ibis Budget Archamps hotel, approx. €800 for the duration of the school.
Financial assistance through the School’s funding mechanism is available to the highest-ranked applicants.
ECTS ACCREDITATION
6 ECTS are awarded by Université Grenoble Alpes to Master and PhD students who complete the whole programme and take part in the oral defense (pitch of innovation project).
If required, UGA will transfer the ECTS directly to the participant’s home university.
