Advanced prognostication in healthcare

Our goal is to continue to improve prognostication in different medical fields and improve these models by incorporating more detailed information and use advanced statistics models to achieve it

Optimizing patient safety

The reason behind this project.
If we can't understand and predict the deterioration, we can't prevent it.

Our projects

We are currently working on improving prognostication for patients admitted to the Intensive Care Unit (ICU). Our next project is about cardiac arrest survivors

The future

Our hope is that these models could be integrated in the electronic journal system and increase that care of our patient. Beta versions of these model will be available to test on our website as they are being developed.

The team


PhD student

Anaesthesia and Intensive Care Medicine. PhD student at Lund University: Intensive care prognostication.


Associate professor

Triple specialist (Internal medicine, Cardiology and Anaesthesia and Intensive care medicine). PhD in mathematical statistics.



Professor of Mathematical Statistics, Head of division

It has been said before,

how computers would changes the health care system. Along with the majority of physicians and nurses in the front line, we are still waiting for the promised change. Yet, we are optimistic that data science will improve the care taking of our patients. So what is the difference this time? An increasing amount of data on each patients are being generated every day combined with an improved statistic methods and data power have made this possible.  Machine learning or the more popular term artificial intelligence, is the term used in general for these statistical methods.

After publishing our research in peer-reviewed journals, we will make some of the these models (beta-versions) available to test on our website.  Our hope is, these models can be integrated in the electronic journal system to increase the safety for our patients admitted to the intensive care department.

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