Machine learning to tailor treatments in mental health
Machine learning to tailor treatments in mental health (AI-MENT)
In psychiatry there is an urgent need for (i) reliable analytic tools to predict response/non-response to psychological treatment and (ii) to develop objective observational and diagnostic tools. Our ambitious aims are to (i) develop novel analyses and methods to predict response to psychological treatment using machine learning in order to avoid over-treatment and to offer personalized treatment, and (ii) improve observation and diagnosis in mental health wards, leading to better treatment and patient safety.
The Data and Artificial Intelligence (DART) group at IE and Trondheim Sleep and Chronobiology Research group (SACR) at IPH/St. Olavs Hospital will cooperate in analyzing existing (i) subjective sleep data from randomized controlled trials (2500 participants) and (ii) objective radar data used to observe patients in an acute psychiatric department (2500 nights). The datasets are of unprecedented size and quality and ideal to train machine learning algorithms on, and further use to develop new analysis methods. The results will have significant potential to change existing treatment and observation strategies in psychiatry.
Read more about the research groups
Trondheim Sleep and Chronobiology Research group (SACR)
Data and Artificial Intelligence (DART) group:
Norwegian Research Center for AI Innovation
Norwegian Open AI Lab