Radboud university medical center opens first healthcare AI labs

Radboud university medical center has started two new initiatives in the field of Artificial Intelligence: Radboud AI for Health and Thira Lab. They are the first two ‘labs’ in the east of the Netherlands that are part of the national Innovation Center for Artificial Intelligence (ICAI) and the first health labs. With these two initiatives, Radboud university medical center and its partners are investing heavily in the application of Artificial Intelligence to health care. In total, twelve PhD research projects, 35 student projects and two AI programmes for health care personnel and researchers will be taking off. 

Thira Lab
Thira Lab is a collaboration between Radboud university medical center, Thirona (a Radboud university medical center spin-off company) and Delft Imaging Systems (a company that develops healthcare applications for vulnerable communities worldwide). At Thira Lab, nine PhD candidates and postdocs from Radboud university medical center are working on AI solutions for medical image analysis of CT scans of the lungs, chest X-rays and retinal scans.  

Radboud AI for Health
Radboud AI for Health is a new collaboration between Radboud University and Radboud university medical center. It is part of Radboud AI, a campus-wide initiative to stimulate public-private partnerships and launch new AI research projects in Nijmegen and the surrounding area. With Radboud AI for Health, Radboud university medical center and Radboud University are working together to develop innovations in the field of Artificial Intelligence that improve health care, make it more affordable and further improve decision-making. 

At Radboud AI for Health, six PhD candidates began working on projects related to AI applications in hospital settings in September. In addition, the researchers at Radboud AI for Health will supervise about 35 projects from Bachelor’s and Master's students every year. Radboud AI for Health will also offer two yearly training programmes specifically for employees of Radboud university medical center, to further train them in the field of Artificial Intelligence and its applications to healthcare.

Step forward
“With Radboud AI for Health and Thira Lab, we are taking a big step forward in the application of Artificial Intelligence to health care. At Radboud university medical center, we work every day with the partners in our network to create workable innovations that improve health care and make it more affordable. Artificial Intelligence plays a crucial role in that effort. With these initiatives, we reaffirm our regional and national cooperation agenda, which we bring together in the TopFit programme”, explains Paul Smits, Chair of the Executive Board at Radboud university medical center. “I am proud that we have successfully launched these initiatives in less than a year; we’re just doing it!”

About ICAI
The Innovation Center for Artificial Intelligence (ICAI) is a national network focused on technological and talent development between knowledge institutes, industry and the government in the field of Artificial Intelligence. www.icai.ai
 
More information on Radboud AI for Health can be found here.
For more information on Radboud AI click here
 
PhD projects
Six PhD research projects started in September. Teams of researchers will be working on developing several AI-applications in healthcare, which will be tested in a clinical setting. In short, the projects consist of developing: 

• A real-time warning system for infection risk of central venous cathethers for patients in the intensive care unit. 
• An AI system to automatically diagnose patients with genetic diseases based on their exome and whole genome sequencing data an AI-based MRI analysis for treatment decision support in patients with chronic degenerative low back pain. 
• A system that can automatically create annotated radiology reports that a patient can understand. 
• An AI algorithm that can help predict vascular function of the brain from short, non-invasive ten-minute recordings of blood pressure, heart rate, and cerebral perfusion.
• A deep-learning system that can predict, on the basis of clinical information, panoramic radiographs, and possibly cone-beam CT, if wisdom tooth removal is recommended.