From AI model to reliable healthcare application with MLOps at LUMC
LUMC
Healthcare
More time for patients starts outside the consultation room.
Good care requires attention to patients. At the same time, demand for care is growing and available capacity is under pressure. Data and AI can support healthcare professionals, leaving more time for direct care.
Challenges,
Healthcare professionals work with different systems, records and information flows every day. As a result, time is lost on tasks outside direct care. The challenge is to preserve more time for patients without compromising the quality of care.
How we support you,
We automate recurring administrative tasks and make relevant information available directly within existing workflows. This means healthcare professionals spend less time recording or searching for information and more time with patients.
These are just some examples of what is possible. The right solution always depends on the challenge and the organisation.
DSL in numbers,
40
Data experts
10+
Years of experience
200+
Projects completed
8,7
Client satisfaction
Get in touch with our experts,
Want to know what we can do for your organisation?
Younes Seghrouchni
Managing Consultant GenAI & Data StrategyE-mail info@datasciencelab.nl
Carmen Wolvius
Managing Consultant Data Science & AIE-mail info@datasciencelab.nl
Stef Stoelwinder
Business DevelopmentE-mail info@datasciencelab.nl
Where we do that,
Latest blog posts,
Read our latest insights here.
Three lessons from our AI projects
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From pilot to production: why most AI projects stall
Many organisations have now run an AI pilot. The model works, the demo gets applause, and then nothing else happens. In our experience, most projects…
Responsible AI: from principles to practice
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The organisations that do this,
Frequently asked questions,
AI can help with repetitive work, such as administrative tasks or processing information. This gives healthcare professionals more time for direct patient care. The aim is not to replace people, but to support them in their daily work.
It starts with solutions that fit the way healthcare professionals work. If a tool adds steps or makes processes more complicated, people are less likely to support it. That is why we develop AI that fits into existing workflows and adds value straight away.
That depends on the application and how it is set up. Privacy, information security and legislation always play an important role. That is why we consider from the outset how data can be processed securely and how organisations can retain control over their information.
AI delivers value when healthcare professionals have more time for patients and spend less time on supporting tasks. The technology is not an end in itself, but a way to improve the quality of care and reduce workloads.
Successful AI takes more than technology. Staff need to understand how a solution works and see that it supports their work. That is why we focus on adoption, guidance and continuous improvement of solutions.
If you work in mental healthcare, read more about <a class="af-inlink-20261110" href="/en/industries/ggz/">data and AI for mental healthcare</a>. For providers caring for people with disabilities, there is a separate page on <a class="af-inlink-20261111" href="/en/industries/gehandicaptenzorg/">data and AI in disability care</a>.