In a collaboration project between Helsinki University Hospital (HUS), Kuopio University Hospital and Turku University Hospital (all Finland), a team of researchers have presented the first artificial intelligence (AI) based algorithm that has the potential to assist in treating patients with severe TBI in intensive care units (ICUs). Patients with the most severe cases of TBI are usually treated in ICUs, however, despite the high-quality care, recent observational studies have reported mortality rates of approximately 30%. Patients who suffer from severe TBI are unconscious, therefore, it is a challenge to accurately monitor their condition. In ICUs many tens of variables, such as intercranial pressure and mean arterial pressure, are continuously monitored to assess the patient's condition. One variable alone could yield hundreds of thousands of data points per day, making it impossible for ICU staff to fully analyze.

A new method developed by Finnish researchers at the University of Eastern Finland, Kuopio University Hospital and Aalto University now provides answers to these questions. Using modelling, the method makes it possible to compare different treatment alternatives and to identify patients who will benefit from treatment. Relying on artificial intelligence, the method is based on causal Bayesian networks. According to Professor Emeritus Olli-Pekka Ryynänen from the University of Eastern Finland, the method opens up new and significant avenues for the development of medical research. "We can now predict the treatment outcome in individual patients and to evaluate existing and new treatment methods. With this method, it is also possible to replace some randomised trials with modelling," Professor Emeritus Ryynänen says.