To foster ties that promote the free exchange of knowledge within the community among experts in AI, non-experts, clinicians, and biologists who utilize ML techniques at all levels of academic careers.
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To consolidate AI and ML expertise within Erasmus MC by sharing cutting-edge technological advances.
To provide tutorials on the elucidation of ML & AI fundamentals and good practices
The AI, Data Science and Big Data age has accelerated the rate of innovation so quickly that most researchers simply can’t keep up. Meanwhile we are contending with an ever-increasing demand for AI applications in healthcare and biomedical research, while there is a shortage of experts.
As artificial intelligence (AI) applications become increasingly widespread and frontier science in machine learning (ML) rapidly evolves, our best chance to accurately and efficiently leverage these tools lies in building a strong and vibrant community that shares knowledge and resources with each other.
Preempting our organization's upcoming efforts to converge forces with TU Delft and Erasmus University Rotterdam, here we build a ground-up Erasmus MC-wide community to consolidate expertise in clinically and biologically relevant artificial intelligence (AI) and machine learning (ML)research within our institute while at the same time increasing awareness for the science and engineering behind AI and ML.
Health care is facing enormous challenges given the ageing of the population. The coming years, an increasing number of people will need care and less people will be available to provide that care. Additionally, the costs of health care will increase substantially. Big data, generated in research and in daily clinical practice, the accessibility of these data, and exploring them by AI/ML is essential to address these challenges. By doing so, we will get a better understanding of biology and disease, and we will have better prognostic and predictive models. This will enable us to provide more individualized and more efficient approaches to help individual patients, and the population, which will contribute to the sustainability of health care.
Stefan Sleijfer
Dean, Erasmus MC
The impact of quantitative AI research will initially feed our wildest imaginations and then go beyond it, generating imaginations of its own that we may not even comprehend.
Chris de Zeeuw
Chair, Department of Neuroscience, Erasmus MC
Expertise and knowledge on AI and big data are rather scattered over multiple clinical and research departments. To really contributed as Erasmus MC to the development and implementation of AI-tools, more coordinated efforts are needed. Bringing people together for exchange and sharing information is a first important step
Aad van der Lugt
Chair, Department of Radiology and Nuclear Medicine, Erasmus MC
AI will be of great help with the challenges that we face in our health care system. As a clinician, I look forward to contribute to the implementation of AI into patient care. I am convinced it will help us improve care for our patients, but different skills and education will be required. For this reason it is important that Erasmus MC, with its strong Convergence policy, is taking a leading role.
Robin Peeters
Chair, Department of Internal Medicine, Erasmus MC
Driving translational AI together across the medical center.