Flagship Data Science for Health

Flagship Data Science for Health

Established in 2014, the Flagship Data Science for Health is a strategic partnership between TU/e (managed by the DSC/e) and Royal Philips Research for responsible research and innovation on methods, techniques, tools and best practices related to Data Science in the context of Health & Healthcare.

This cooperation in responsible research and innovation takes place on a bigger scale than usual academic-industrial partnerships. It is not only scoped over a longer time frame, but also goes beyond topical interaction and has programs for various sections of the health value chain. By structurally aligning our efforts and sharing results, we expect to maximize the results in an integral manner, and to make a significant contribution to meaningful innovation in data science for optimal healthcare of people and the use of data for new propositions.

We also expect to enhance human capital development and to strengthen the position of TU/e and Royal Philips in the related innovative science & technology landscape. We will jointly develop support structures to set agendas and influence programs for public private partnerships and public funding and communicate to shared stakeholders. We will strive to be relevant with a unique proposition, to demonstrate a readiness for change when business/market priorities shift and to enable regular reviews to assess the continued value for both parties.

Based on a long-term strategic research & innovation agenda, the Flagship basically is a portfolio of related, coherent programs. These programs consist of interrelated projects covering the full range of descriptive analytics, predictive analytics and prescriptive analytics of people (not necessarily patients), processes and equipment.

Within the flagship there are four programs:

  1. Data-Driven Value Proposition: Investigates the opportunities for learning from data gathered from products, consumers and their interaction;
  2. Healthcare Smart Maintenance: Investigates how to use event data to predict and optimize condition-based maintenance policies for complex machines;
  3. Optimizing Healthcare Workflows: Combines process mining and visualization techniques to optimize pathology but also radiology workflows;
  4. Continuous Personal Health: Investigates how to empower people to gain insights in their physical health status and adopt habits that reduce health risks and promote good health.

In the context of the Flagship’s specific research & innovation programs there is a close collaboration between a number of research groups at Royal Philips Research and a number of research groups of various departments of TU/e, including the Department of Mathematics & Computer Science, the Department of Electrical Engineering and the Department of Industrial Engineering & Innovation Sciences.

In 2016 we concluded the recruitment and selection of the initial batch of early-stage researchers (PhD) and we finalized the second edition of the strategic research & innovation agenda. Based on an earlier version of the agenda and initial results of the various projects, researchers also initiated a number of joint proposals for new research and innovation projects in the context of relevant regional, national (e.g. NWO, STW) and European (e.g. Eureka ITEA, Horizon 2020, incl. EIT Digital/EIT Health) programs. A significant number of these proposals was granted.

In the context of the Flagship’s specific research & innovation programs there is a close collaboration between a number of research groups at Royal Philips Research and a number of research groups of various departments of TU/e, including the Department of Mathematics & Computer Science, the Department of Electrical Engineering and the Department of Industrial Engineering & Innovation Sciences.

In 2016 we concluded the recruitment and selection of the initial batch of early-stage researchers (PhD) and we finalized the second edition of the strategic research & innovation agenda. Based on an earlier version of the agenda and initial results of the various projects, researchers also initiated a number of joint proposals for new research and innovation projects in the context of relevant regional, national (e.g. NWO, STW) and European (e.g. Eureka ITEA, Horizon 2020, incl. EIT Digital/EIT Health) programs. A significant number of these proposals was granted.