Intelligence, the next challenge in system complexity?
09 april | Auditorium TU/e Eindhoven, Eindhoven | ESI | Gratis | Website
High-tech systems are integrating more and more intelligence, which increases engineering complexity. At the 2019 ESI Symposium we will discuss the challenges this presents and initial directions for managing, and coping with, the growing complexity.
We would like to invite you to join the symposium. The event features a varied program with interactive sessions inspired by contributions from industrial and academic speakers. Moreover, there will be plenty of networking opportunities on the innovation market. Please register now.
Keynote speaker academy: Edward A. Lee, Professor in Electrical Engineering and Computer Sciences, University of California, Berkeley
Keynote speaker from industry: Henk van Houten, CTO and Head of Research for Royal Philips
Title: Digitalization and AI in support of Value Based Care
Healthcare costs are exploding, medical staff are overburdened, and patients live longer with (multiple) chronic conditions. These are just a few of the many challenges healthcare systems across the globe are facing. Philips has adopted the quadruple aim as its yardstick for innovations which seek to alleviate these challenges. This approach ensures that we measure our innovation in terms of the impact on improving clinical outcomes, reducing cost, and enhancing the patient and staff experience.
Digitalization is a key enabler for solutions addressing the quadruple aim. Adoption of (hybrid) Cloud platforms and the Internet of Things is unlocking data at an unprecedented scale. Making sense of all this data calls for smart algorithms, and tailored deployment platforms embedded in the workflow of the healthcare professionals. Artificial Intelligence has the potential to play an important role in this. Philips positions AI as Adaptive Intelligence – technology that adapts to people in their daily context and augments their capabilities. Combining data-based adaptation with anatomical and biological science captured in models of organs, like the heart, is a powerful way to support precision diagnosis and image guided therapy. Such models can also be used to connect the dots across the health continuum, ultimately evolving into a digital twin of the patient. This we believe will be a powerful complement of electronic medical records, and a key ingredient in seamless delivery of collaborative care.
- Digital Twinning
How can digital twinning drive design and engineering innovation?
- Learning systems
How to exploit system data for operational excellence?
- Architecting intelligent systems
Is a paradigm shift needed in architecting intelligent systems?
- Diagnostic reasoning
Model based reasoning to support diagnostics in complex systems
- Acceptable AI
How to obtain trust in systems with AI components?
- Future system engineers
What does future systems engineering look like? Will the rise of intelligent systems threaten or augment SE practices?