Next steps for Danish-Israeli collaboration on AI and health data
09 december 2020
In November, we gathered some of the greatest capabilities within AI in radiology from Denmark and Israel to discuss current barriers and opportunities in implementing algorithms in a clinical setting together with the collaborating scale-ups Radiobotics and Donnect.
The goal was to demonstrate how far Danish and Israeli hospitals have come with implementing AI algorithms within radiology and potential next steps for a collaborative approach and joint vision towards the development and responsible use of AI for the benefit of citizens and innovators.
The challenge – a burning platform
Since the volume of imaging has increased rapidly and the number of radiologists has decreased, a status quo has emerged characterized by growing workloads for overburdened physicians and subsequent bottlenecks. Also, there is a constant strive to provide faster and better services to patients and ensuring rapid diagnostic response time to patients in critical condition.
Three specific learnings and recommendations emerged for future work:
- Going from local to global: There is still work to be done in both Denmark and Israel when it comes to implementing full-scale AI solutions. One of the main challenges is a fragmented data landscape, data silos, and lack of standards. Therefore, there is a strong need to focus on the quantity and quality of data and interoperable datasets for the purpose of AI/ML/deep learning.
- Harmonized infrastructure: Developing a common infrastructure agenda concerning ethical and responsible AI and data use that takes important issues such as anonymization and privacy into account as well as reducing barriers for delivering the full growth and development potential offered by AI.
- Facilitate transfer learning and strengthen digital competences: Developing and training deep-learning models that can simulate algorithms before actual clinical implementation. In this respect, AI education of radiologists is key to clinical implementation and adaption.
Two scale-ups gave two perspectives
Radiobotics is a Danish scale-up focusing on developing and implementing stellar machine learning algorithms that supports doctors in analysing medical images in routine cases and making the right decisions. Ultimately, enabling the doctor to focus on complex cases and tasks.
“I think Rambam's experience of working with companies and startups in this space is really fascinating with interesting collaboration opportunities, also between RAIT and Rambam. It will be interesting to hear more about their experience when it comes to collaboration models with for example Google and Viz.ai”, Martin Axelsen, CTO, Radiobotics
The Israeli startup Donnect has developed an algorithm and platform for matching kidney donors and patients nationally and internationally according to local regulations. Donnect has worked with Rambam to determine accurate platform criteria.
“The vision of the Danish innovation center is unique and enables great opportunities for Donnect. I anticipate collaboration between Israeli and Danish innovators as part of this ground breaking ecosystem”, Tal Cohen, CEO, Donncet
The Danish radiology departments in the capital region of Denmark have founded a Radiology AI-test center (RAIT) that contains all relevant specialties to validate, test, and clinically implement AI technology.
The idea and ambitions are to roll out the RAIT strategy to the rest of Denmark’s departments of radiology in a joint venture and welcome private companies from Denmark and internationally to test and validate new AI-based technologies.
"With the RAIT center, we aim at being a Danish and potential Nordic reference site for clinical studies and innovation within the cross-field of radiology and AI-based technology. Soon, we will hopefully be able to offer all projects at RAIT access to one grand data pool with past and future radiological and imaging data while respecting both GDPR and patient data security”, Mikael Boesen, Professor at Department of Radiology Bispebjerg and Frederiksberg Hospital
Rambam has built a strong innovation platform for collaboration with startups and other stakeholders in developing new healthcare solutions. Rambam has particularly excelled in the development and testing of AI-based and other digital solutions, also in close collaboration with the world-leading Technion Institute of Technology. Rambam is currently in the process of establishing an AI centre for collaboration with the industry.
Rambam welcomes Danish startups and corporations to test and validate AI solutions at the hospital. Rambam experts also have extensive experience in advising companies in technology development and adaptation.
"The AI Center of Excellence at Rambam aims to explore machine learning answers for clinically important questions, expose hidden information through deep data analytics, and assist health care providers and their patients using Radiomics to personalize medical decision making and treatment", Eyal Bercovich MD and Marcia C. Javitt, MD FACR Department of Imaging, Rambam Hospital
"With like-minded forward-thinking groups like the Danish Radiology Test Center, collaboration is bound to inspire innovation. Together we can increase both the quantity and quality of the data pool, reduce bias, and improve interoperability. Startups will thrive with exposure to a team of content matter experts, data engineers, and academic front line clinical radiologists. Putting inventors in touch with international healthcare industry partnerships will help to accelerate production, growth, and success. When it comes to AI, 'all of us is better than each of us", Marcia C. Javitt, MD, Director of Medical Imaging, Rambam Health Care Campus
See the webinar:
Click here to see the webinar.
Want to know more about Danish-Israeli industrial R&D cooperation opportunities within AI?
Louise Buch Rosenlund
Danish Life Science Cluster / Data Saves Lives
30 33 25 80
Louise Vibjerg Thomsen
Senior Innovation Officer
Innovation Center Denmark, Tel Aviv
+972 (0) 54 8080 369