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 healthcare is growing and available capacity is under pressure. Data and AI can support healthcare professionals, leaving more time for direct patient care.
Challenges,
Healthcare professionals work with different systems, records and flows of information every day. As a result, time is lost to tasks outside direct patient care. The challenge is to keep more time available 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 entering records or searching for information, and more time with patients.
These are just a few examples of what is possible. The best solution always depends on the challenge and the organisation.
Data Science Lab at a glance
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
Claudia Sulsters
Managing Consultant Data EngineeringE-mail info@datasciencelab.nl
Carmen Wolvius
Managing Consultant Data Science & AIE-mail info@datasciencelab.nl
Where we do that,
Latest blog posts,
Read our latest insights here.
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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 leaves 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 an application adds steps or makes processes more complicated, support for it fades. That is why we develop AI that fits into existing workflows and adds value from the outset.
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 ease 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.