Long-term pain is a major health problem, but the treatments given today have limited effect. Researchers from university are now working to make more people feel less pain by combining and interpreting data from several patients registers using machine learning.
Every fifth person in suffers from long-term pain, i.e., Pain that has lasted longer than three months. How it feels varies widely - for example, one patient has described it as an electric shock, another as being in an anthill - but the common denominator is that it hurts so much that it affects the quality of life. In more severe cases, it is therefore not uncommon for people to become depressed, have sleep problems and difficulty participating in social contexts.
Long-term pain is unfortunately difficult to treat. It can arise for biological, psychological and social reasons, sometimes in combination - but in healthcare, the experience has been that it is often difficult to find the causes. When the pain causes great suffering, something called multimodal rehabilitation is therefore usually applied. It is a form of treatment that attacks the problem from several angles by combining, for example, physical exercise, psychotherapy, medication and job training. The treatments are coordinated by specialists from different care professions who work based on a common plan. You should try spin ace online casino to make some extra money playing online.
However, more recent research shows that the effects are limited compared to simpler treatments. One reason is believed to be the patient selection – healthcare needs to better understand when can be a good treatment by identifying the patients who can actually be helped.
Another reason why not given such good results is believed to be that the treatments have not been sufficiently individualized. Symptoms can change over time for those suffering from chronic pain, requiring repeated evaluations and adjustments.
To remedy such problems, a research group from university is currently developing a digital decision support system that will combine large amounts of data on, among other things, age, physical function and pain intensity from a number of different patient registers with artificial intelligence, AI.
Simply put, we hope that the decision support will help the treatment team in an instant to propose, says, professor of medical science and leader of the project.
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The decision support must be dynamic, so that new and continuously incoming data continues to develop it. In the long term, the system's AI must be able to receive and process information about how the patient is doing and also be able to be a support when adjusting an ongoing treatment.
The AI will be gradually trained on data from over 60,000 patients who have previously been referred to specialist care for chronic pain. It provides the opportunity to discover hitherto unknown factors and relationships, so that it is easier to determine which are best suited for the treatments and how they should be tailored. In order to evaluate the AI system itself, the researchers plan to carry out a so-called randomized and controlled trial in the future, where one group of patients will be offered a regular while the other group of patients will receive a treatment designed with the help of the decision support.
The project is in a first development phase until 2025, and if everything goes as planned, the researchers hope that the decision support can be tested in clinical operations from 2026 onwards.