The algorithm enables monitoring of prognosis in patients with traumatic brain injury (TBI) during intensive care, even though the patient is unconscious.

Neurosurgery resident Rahul Raj at HUS Helsinki University Hospital has been recognised by The European Association of Neurosurgical Societies for best clinical paper 2020 for his research ”Machine learning-based dynamic mortality prediction after traumatic brain injury” published in Nature’s Scientific Reports.

Treating TBI patients in the intensive care unit (ICU) is challenging for main three reasons, says Rahul Raj.”First of all, the patient is usually unconscious. Second, there is no objective way to measure the severity of the brain injury. Third, we don’t objectively know how different treatments impact the prognosis of the patients.”The recognised research paper shows a promising start for future use of machine-learning based solutions in intensive care. It is the world’s first algorithm based on machine-learning, that can help clinicians to quantify the dynamic prognosis of patients with TBI. In practice, this means that there will be a scale of 0 to 100 to describe the probability of death caused by the brain injury.

Health Capital Helsinki