Artificial Intelligence-based Algorithm for Intensive Care of Traumatic Brain Injury
Traumatic brain injury (TBI) is a significant global cause of mortality and morbidity with an increasing incidence, especially in low-and-middle income countries. The most severe TBIs are treated in intensive care units (ICU), but in spite of the proper and high-quality care, about one in three patients dies.
Patients that suffer from severe TBI are unconscious, which makes it challenging to accurately monitor the condition of the patient during intensive care. In the ICU, many tens of variables are continuously monitored (e.g. intracranial pressure, mean arterial pressure and cerebral perfusion pressure) that indirectly give information regarding the condition of the patient.
However, only one variable, such as intracranial pressure, may yield hundreds of thousands of data points per day. Thus, it is impossible for the human brain to comprehend the resulting millions of daily collected data points from all monitored data. This is why researchers at Helsinki University Hospital (HUS) started to develop an artificial intelligence (AI) based algorithm that could help doctors treat patients with severe TBI. At its best, such an algorithm could predict the outcome of the individual patient and give objective data regarding the condition and prognosis of the patient and how it changes during treatment.
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