Limburg welcomes first ICAI Lab for the development of AI for patient care

Knowledge institutions from Limburg will join forces with local parties in healthcare and IT. The first ICAI Lab in the region – the ICAI Brightlands Smart Health Lab – is committed to making breakthroughs in patient care by developing and deploying artificial intelligence.

ICAI Brightlands Smart Health Lab

With the arrival of the ICAI Brightlands Smart Health Lab, Limburg joins the national network of ICAI Labs. In this new lab, researchers from Maastricht University and Zuyd University of Applied Sciences will collaborate with healthcare providers, the Netherlands Comprehensive Cancer Organisation, medical IT service provider ilionx, and several Brightlands campuses and organisations.

The activities of the new lab span the entire process from the development to the deployment of artificial intelligence in healthcare. Among other topics, the lab focuses on preparing medical data so that it can be used anonymously for ‘training’ artificial intelligence. Other key activities of the ICAI Brightlands Smart Health Lab include the development of artificial intelligence and putting the technology into practice. The lab specifically focuses on artificial intelligence that can predict how a patient’s disease will develop. In this way, the technology can help map out treatment plans for diseases like cancer.


Professor Andre Dekker, one of the lab’s academic directors alongside Dr. Rianne Fijten and Dr. Alberto Traverso, considers the collaboration between all parties as crucial for the success of their joint vision for the future. Dekker: “Bringing together knowledge and data from very diverse parties in the Brightlands ecosystem is precisely what allows us to conduct relevant research, develop real solutions and put these into practice.”

Responsibly connecting data

Dekker and his team bring their expertise in responsible sharing of privacy-sensitive medical data. The ICAI Brightlands Smart Health Lab thereby builds on their work on the Personal Health Train: a network that allows healthcare providers to learn from each other’s data, but in which data never leaves the host institution’s management and through which the privacy of patients is preserved.

Dr. Rianne Fijten: “Data is often an abstract concept for researchers, but it comes from real people. That is why careful handling of privacy-sensitive medical data is very important to us.”

Partners in the ICAI Brightlands Smart Health Lab

The ICAI Brightlands Smart Health Lab is a collaboration between Maastricht University, Zuyd University of Applied Sciences, Maastro Clinic, Maastricht UMC+, ilionx, Netherlands Comprehensive Cancer Organisation (IKNL), Brightlands Institute for Smart Society, Brightlands Smart Services Campus, Brightlands Maastricht Health Campus and AI Hub Brightlands.

Episode #13 with Laura Hollink

In aflevering #13 van Snoek op Zolder vertelt Laura Hollink van het Centrum voor Wiskunde en Informatica (CWI) en het Cultural AI Lab, over de ICAI samenwerking van CWI, TNO, de UvA en de VU, het KNAW Humanities Cluster, de Koninklijke Bibliotheek, het Nederlands Instituut voor Beeld en Geluid én het Rijksmuseum, over hoe BERTje het mkb kan helpen om ook met AI te starten, over white boxing the black box, over hoe AI interessant wordt gemaakt voor gebruik door geesteswetenschappers en over een eerlijk en onbevooroordeeld aanbevelingssysteem voor boeken die je kunt lenen.

Over Snoek op Zolder

Snoek op Zolder is de tweewekelijkse wetenschapspodcast van ICAI en de Nederlandse AI Coalitie (NL AIC). Hennie Huijgens duikt met een onderzoeker van een publieke of private organisatie in de wereld van kunstmatige intelligentie. Zijn belangrijkste vraag is ‘wat is de stand van zaken in AI onderzoek, en wat betekent dat voor mij en voor de samenleving?’

ICAI Interview: Improving patients’ vision and hearing with the help of AI

Umut Güçlü and Yağmur Güçlütürk run the Donders AI for Neurotech Lab together. With the help of machine learning techniques the lab tries to develop solutions that restore sensory and cognitive functions. These can be, for example, tools that improve hearing and vision, but they can also be solutions to help paralyzed people communicate or to suppress epilepsy. Güçlü and Güçlütürk: ‘We use an immensely high level of interdisciplinary exchange – with engineers, experimentalists, surgeons and ethicists – to achieve our goals.’

Umut Güçlü
Yağmur Güçlütürk

Donders AI for Neurotech Lab is a collaboration between the Donders Institute for Brain, Cognition and Behaviour, Radboud University, Phosphoenix, Advanced Bionics, Oneplanet Research Center and Abbott.

Dr. Umut Güçlü is lab manager of ICAI’s Donders AI for Neurotech Lab and is assistant professor of AI at Donders Institute for Brain, Cognition and Behaviour.

Dr. Yağmur Güçlütürk is lab manager of Donders AI for Neurotech Lab and is assistant professor of AI at Donders Institute for Brain, Cognition and Behaviour

First of all, what are your roles as lab managers?

‘Together, we are responsible for the day-to-day running of the lab. That is, we coordinate communication and research activities as well as supervising the Master students and the PhD candidates in the lab.’

The Donders AI for Neurotech Lab is working on an interesting combination: AI combined with neural implants. What kind of things is the lab working on now?

‘We develop machine learning methods for brain reading and brain writing technologies that restore cognitive and sensory function. We try to answer questions like: How can we use machine learning methods to optimally stimulate the brain via cortical implants? How can we improve the speech understanding of the users of cochlear implants? (Cochlear implants are small electronic devices that electrically convert sound into electric pulses to restore or improve someone’s hearing, red.) Another project revolves around the development of techniques for decoding and regulation of cognitive states like emotions, attention and stress.’

What are the opportunities and what are the challenges?

‘Tens of millions of people suffer from blindness and hundreds of millions of people suffer from deafness across the world. These losses can be devastating and greatly reduce one’s autonomy and quality of life. On top of that, large economic losses to society are accrued due to reduced workforce participation and burden of care. Thus far, however, previous implants have provided limited recovery of function. Hence, several crucial technological advances are required before effective, safe, permanent solutions are available to patients. Alleviating these challenges is our biggest opportunity.’

In what way can AI be used in neurotechnology?

‘AI has made huge leaps forward, allowing breakthroughs in object recognition, language processing, and even autonomous driving. With AI, a computer learns on its own from data, and develops an “answer” that can be used autonomously by a mechanical or electrical device. Here we use AI to improve the performance of brain-reading and brain-writing, enabling the automatic sensing of a signal in the outside world, or from a brain recording, that can then be directly fed to a neurostimulator for disorders of vision, movement, hearing, communication, and for the prevention of debilitating seizures. Our team is making use of the latest AI techniques in neural networks and probabilistic inference developed towards optimal signal detection, useful for the neurostimulation applications requiring rapid, and adaptive, brain-reading and brain-writing applications.’

And in what way is your lab’s approach different from other research?

‘I would say: the immensely high level of interdisciplinary exchange required to achieve our objectives. Given the scale and sophistication of our undertaking, we work together with different companies, knowledge institutes, patient organizations and an advisory board. For example, we closely collaborate with engineers who develop hardware, with experimentalists who use animal models, surgeons and physicians who perform clinical trials as well as with ethicists who keep societal implications in check.’

What kind of implants in this area are already being used by patients?

‘There are already hundreds of thousands of cochlear implant users in the world. While there is still room for breakthroughs, it is a mature technology in common use. In contrast, the technology readiness level of visual cortical implants is relatively low, having only been demonstrated as a proof-of-principle in recent studies with great leaps in the horizon. For example, one of our close collaborators Eduardo Fernández from the University Miguel Hernández in Spain recently demonstrated how an array of penetrating electrodes can produce a simple form of vision by conducting a series of experiments with a 58-year-old blind volunteer who has been blind for the last 16 years. The blind volunteer was implanted with 100 microelectrodes in the visual cortex of the brain and wore camera eyeglasses. A software was used to transform what the camera captures to how the electrodes stimulate the neurons in the brain. As a result, images comprising white points of light known as “phosphenes” were created directly in the mind of the volunteer who was able to identify lines, shapes and simple letters evoked by different patterns of stimulation.’

Interested to find out more about the research of this lab? On December 16, Donders AI for Neurotech Lab will talk about their state-of-the-art work during the lunch Meetup of ‘ICAI: The Labs’ on AI for Cognition in the Netherlands. Find out more and join!

Episode #12 Snoek op Zolder

In deze aflevering van de Snoek op Zolder podcast vertelt Marcel van Gerven van de Radboud Universiteit en het het Donders AI for Neurotech Lab, over machine learning methods for brain reading and brain writing technologies, AI over vijf en vijftien jaar, “krijgen we straks robots met neurale implantaten en AI technologie?”, “AI, HBO-studenten en het mkb” en “wie was Frans Donders?”

Over Snoek op Zolder

Snoek op Zolder is de tweewekelijkse wetenschapspodcast van ICAI en de Nederlandse AI Coalitie (NL AIC). Hennie Huijgens duikt met een onderzoeker van een publieke of private organisatie in de wereld van kunstmatige intelligentie. Zijn belangrijkste vraag is ‘wat is de stand van zaken in AI onderzoek, en wat betekent dat voor mij en voor de samenleving?’

Current developments in ICAI labs: e/MTIC AI Lab

The e/MTIC AI-Lab focuses on improving personalized treatment in healthcare. In this article the lab provides an update of their latest state-of-the-art initiatives: the Health Data Portal and the ‘From Bench to Bedside’ project.

Future diagnostics, treatments and prevention in healthcare are supported by AI systems that are trained by large data sets. This requires a professional and structural approach for a data platform, not only from a functional ICT perspective but also from a non-functional perspective in data and cyber security, privacy, liability, robustness, ownership, access control and many other aspects.

e/MTIC AI works with a unique mixture of industry, clinical partners and researchers to increase the value of AI for clinical practice and improve personalized treatment. The research and innovation, conducted by the five e/MTIC partners, are increasingly ‘data driven’. Breakthrough innovations are based on insights obtained from combining and analyzing data sets from various domains and sources.

e/MTIC Health Data Portal

To safely share the medical data from these multiple institutions, e/MTIC established a scalable collaboration platform called the Health Data Portal (HDP). The e/MTIC HDP is the first health data platform in the Netherlands that will be able to bring together data from different disciplines and institutes to speed up health innovations by facilitating large amounts of data from complementary sources to be stored, shared and researched in a secure, reliable and privacy-respecting way.

This year the e/MTIC HDP has progressed sufficiently to take the next step in the direction of integration in national health infrastructures. With this, it will play an important role in the national network of the Health-RI project, financed by the National Growth Fund.

In practice, with the e/MTIC Health Data portal, PhD students can spend more time on research instead of arranging and collecting data and sorting out all kinds of legal aspects.

From Bench to Bedside

With such solid data infrastructure in place, e/MTIC – Fast track to clinical innovation – takes shape in many projects, amongst which ‘From Bench to Bedside‘. This project focuses on accelerating digital innovation by co-creating in 6 months innovation cycles with a multidisciplinary team (Catharina Hospital, Philips Research and the TU/e).

Newly developed solutions need to have a practical application in healthcare and preferably implemented quickly and as impactfully as possible. However, every innovation has a long journey, from the first idea to a product or a solution. This innovation circle can be reduced considerably by using existing and new data combined with AI. The Bench to Bedside methodology covers 4 phases: identifying clinical requirements, identifying technical requirements, followed by building and testing a proof of concept. These 4 phases come in form of innovation cycles of only six months.

e/MTIC is a large-scale research collaboration between the Catharina Hospital, Maxima Medical Center, Kempenhaeghe Epilepsy and Sleep Center, Eindhoven University of Technology and Philips Eindhoven.

ICAI Interview with Marjan van den Akker: Using algorithms to future-proof the Dutch public transport system

The Utrecht AI & Mobility Lab addresses complicated planning puzzles in public transport. Marjan van den Akker: ‘We are in a quadrangle with learning from data, optimization algorithms, agent-based simulations and human-centered AI.’

Marjan van den Akker (foto: GSNS, Utrecht University)

Marjan van den Akker is Scientific Director of ICAI’s Utrecht AI & Mobility Lab and is Associate Professor at the Information and Computing Science department of Utrecht University.

Utrecht AI & Mobility Lab is a collaboration of Nederlandse Spoorwegen (NS), Prorail and Qbuzz.

There are quite a few problems with public transport in the Netherlands right now. Mainly, that it’s overloaded. What kinds of problems is the AI & Mobility Lab addressing?

Marjan van den Akker: ‘One of the things we are investing is the planning for the service locations of the Dutch railways. At these locations the trains are parked when they are not running. They are cleaned there and small maintenance check and operations are carried out. These locations are in big city areas, close to the railway stations. Because of the enormous passenger growth, they are really overloaded.

And with the Dutch bus company Qbuzz we look into issues related to the energy transition and electric vehicles. Currently an electric bus cannot drive all day without charging, so you have to incorporate this in the schedule. We have to answer questions like: Do we charge often, which is good for the batteries? Or do we charge less, which makes the scheduling less complicated?’

How can these problems be tackled with AI techniques?

‘What we see at the service locations of the NS is that the problems are so complex that we need a hybrid approach. We have to combine optimization algorithms and learning algorithms. Another challenge is that all these planning algorithms are incorporated in decision support systems. They are used by humans in two ways. One way is on a strategic and policy level where people use the algorithms to estimate capacities of the transport system. The other way is in the actual operations where human planners need to work together with the system. The system does all these complicated calculations and suggests solutions, but it may happen that the human operator has to alter the plan because of a sudden change.’

Is this approach unique in the Netherlands?

‘Yes, to have all these different approaches in one computer science department is rather unique. Most places in the Netherlands use Operation Research in a mathematical way. But we use a hybrid approach of computational AI and Operation Research algorithms.’

Can you already tell us something about the lab first results?

‘We are a long-term lab and it’s founded on the bases of research that has already been running for some years. Four years ago one of our PhD students, Roel van den Broek, started on an algorithm for the planning of the service locations of the NS. The NS is currently running a pilot with this algorithm and intends to take it into use. This algorithm plans everything on the service locations: where the arriving trains have to be parked, when they go into the maintenance facility and the cleaning platform and which train units have to be coupled or decoupled. And that all has to be arranged in this highly packed area.’

You have been a technology consultant at the National Aerospace Laboratory for five years. Does that experience help you in working with companies?

‘Yes, I think I have more insight in the application domain. The goals of companies are a bit different from the goals of the scientists. A company of course, is mostly interested in the results and not in the paper that we write.’

What are the ambitions of the lab?

‘We want to extend in the field of logistics. We have conversations with new companies that are involved with mobility as a service. For example a company that organizes the use of shared cars and bikes and also gives travel advice. We try to connect as much as possible with all kinds of organizations in the new changing mobility area.’

Utrecht University has founded the AI Labs, of which the Mobility & AI Lab is part, and is ambitious in the field of innovative AI techniques. Can you tell us something about these plans?

‘Labs are a good instrument to achieve research. The UU started out with the Police Lab a few years ago, and that was very successful. So we are founding AI labs now in all kinds of areas. Besides the mobility theme, we are working on setting up labs in the fields of sustainability, health, media and the humanities. In Utrecht we can provide multidisciplinary research, in a way that a university of technology couldn’t, because we have more possibilities to take a human-centered approach.’

On November 18, 2021, the Utrecht AI & Mobility Lab will talk about their current work during the lunch Meetup of ‘ICAI: The Labs’ on AI and Mobility in the Netherlands. Want to join? Sign up!

Listen to the newest episode of ‘Snoek op Zolder’ podcast

Snoek op Zolder is the biweekly science podcast of the Dutch AI Coalition (NL AIC) and ICAI. In this week’s episode #11, host of the podcast Hennie Huijgens talks to Jan-Jacob Sonke on the use of AI for radiotherapy in the Netherlands Cancer Institute, ‘sloppy cancer cells’, the role of doctors and patients in AI research, and more. The podcast is in Dutch.

Future Impact joins ICAI Launch Pad

Future Impact, a tech-job focused platform for young talent, and ICAI will collaborate in the Launch Pad programme. Launch Pad is initiated by ICAI to connect young AI talent to the Dutch ecosystem. Together with Future Impact and the Dutch AI Coalition, ICAI wants to further expand Launch Pad into a pro-active support programme for AI careers in the Netherlands.

ICAI believes that the Netherlands offers great opportunities in the field of AI, but that AI talent and the organizations that need this talent are not yet able to find each other. The aim of Launch Pad is to connect AI talent to the Dutch ecosystem by providing a matchmaking process between AI-PhD students and Dutch companies looking for AI talent. Future Impact will fulfill the role of matchmaker.


All partners in the Launch Pad collaboration have a specific expertise and role in the matchmaking process. ICAI will use its network of ICAI labs to connect with PhD students who are about to enter the labor market. Future Impact will focus on the recruitment and matching of young AI talent. And the Dutch AI Coalition (NLAIC) will provide a network of organizations who are involved with AI in the Netherlands.

Awareness of AI opportunities

The Launch Pad programme wants to create awareness amongst students of the possibilities in the Dutch ecosystem. At the moment, many trained PhD students go (back) abroad, without being aware of the possibilities and favorable living conditions in the Netherlands. ICAI wants more students to stay in the Netherlands after pursuing their PhD.

Future Impact as matchmaker

Future Impact will act as matchmaker and introduce AI talent to Dutch based partners. The platform has a broad network of relevant organizations looking for AI talent. In addition to the matchmaking role, Future Impact offers support throughout the whole matchmaking and application process. This includes coaching candidates in finding their areas of interest, helping them to prepare for job interviews and negotiating contracts.

ICAI mission

One of the missions of ICAI is to create and nurture a national AI knowledge and talent ecosystem. ICAI Launch Pad is the next practical step in carrying out this mission.

Registration open now! ICAI Day: A Deep Dive into AI

On the 27th of October ICAI organizes the ICAI Day: A Deep Dive into AI. This hybrid event will take place on location in Den Bosch and online. The focus of this ICAI event will be on the technological side of AI. Registration for the event is now open for everybody who is interested. You can register here.

Together with the ELSA Labs community of NLAIC, we organize a lunch event as part of the ICAI day for all the labs. In small table settings we will deep dive into specific area’s and how to work on AI with trustworthiness integrated in the technology. Introductions will come from the Police Lab and ELSA Lab. You must be physically present to attend this part of the programme.

We have speakers from outside and inside the labs who will dive into the latest technologies of AI and show work on Geometric Deep Learning: from Euclid to drug design (Michael Bronstein, Imperial College & Twitter) and graph convolution networks (Xie Weiyi, Radboud MC/Thira Lab). Finally our experts in the labs, from academia and industry, will share insides on lessons learned from the collaborations in the ICAI labs.

The event will take place in two parts:

12:00 – 13:30 Part 1: Lunch table discussions
With introductions of:
Heleen Rutjes (TU Eindhoven, ELSA Labs)
Maurits Bleeker (UvA, Police Lab)
Sarah Ibrahimi (UvA, Police Lab)

Topics of the lunch table discussions:
– Inclusive society with data engineering
– Autonomous systems in mobility
– Robotics & autonomous agents
– Computer vision in healthcare
– Using AI in education and governmental org.
– Online personalization and impact

13:45 – 17:00 Part 2: ICAI plenary event
13:45 – 14:00 Welcome by chair Nathan de Groot and director of ICAI Maarten de Rijke
14:00 – 14:45 Keynote Michael Bronstein Geometric Deep Learning: from Euclid to drug design (Twitter, Imperial College)

14:45 – 15:00 Break

15:00 – 15:30 Lecture Xie Weiyi (Thira Lab) – Graph Attention Networks for airway labeling
15:30 – 15:35 Short videos of different ICAI labs
15:35 – 16:20 Discussion table ICAI labs –Lessons learned in collaboration:
Elvan Kula (ING, AI for Fintech Lab),
Georgios Tsatsaronis (Elsevier, Discovery Lab),
Cees Snoek (UvA, QUVA, AIM & Atlas Lab)
16:20 – 16:30 Closing words

16:30 – 17:30 Drinks

We look forward welcoming you at our event!

Register here

LTP Program ROBUST wins NWO support

ICAI is very proud to be able to expand the network of ICAI with the LTP ROBUST program “Trustworthy AI systems for sustainable growth”, supported by NWO in the new Long Term Program with €25 million.

AI technology promises to help with many tough societal challenges. For the technology to be adopted and benefit everyone, it is essential that the AI systems that we develop are trustworthy. The ROBUST Long-Term Program addresses this challenge and gets the opportunity to build the program.

First and foremost, ROBUST focuses on attracting talent to work on the challenges of trustworthy AI. Talent is the core of any AI ecosystem. Second, it makes trustworthy AI research and innovation a shared responsibility between knowledge institutes, industry, governmental organizations, and other societal stakeholders. And third, it practices learning by doing in the Dutch context, through use-inspired research, connections with startups and SMEs, and an extensive knowledge sharing efforts.

17 new ICAI labs

The ROBUST program builds on ICAI, the Innovation Center for Artificial Intelligence. It intends to add 17 labs to ICAI’s current ecosystem of 30 labs, in areas as diverse as health, energy, logistics, and services. The labs that make up ROBUST are driven by economic opportunities and contributions to the UN’s sustainable development goals. They will develop AI-algorithms that advance the state of the art in accuracy, reliability, repeatability, resilience, and safety of AI algorithms – all essential hallmarks of trustworthy AI.

ROBUST is a collaboration of 21 knowledge institutes, 23 companies, and 10 societal organizations. ROBUST is supported by the Netherlands Organisation for Scientific Research (NWO) and the AiNed National Growth Fund Investment Program.

Project team

The project leader for the ROBUST program is prof. Maarten de Rijke of the University of Amsterdam and ICAI. The co-applicants are prof. Mark van den Brand (Technical University Eindhoven), prof. Arie van Deursen (Delft University of Technology), prof. Bram van Ginneken (RadboudUMC), dr. Eva van Rikxoort (Thirona), prof. Clarisa Sánchez Gutiérrez (University of Amsterdam), and prof. Nava Tintarev (Maastricht University).

Contact: Esther Smit,

Read the NWO press release here.