Acute ischemic stroke is a major disease and one of the leading causes of adult death and disability. Brain tissue infarcts permanently within hours after onset and rapid reperfusion treatment is therefore of utmost importance. Current methods to predict the tissue outcome are too simplistic. In this project a more advanced approach using deep neural networks to utilize the information from previous patient developments was established and compared to current state-of-the-art. The predictions from the deep neural networks were showed to be superior to the state-of-the-art method improving prediction accuracy and hence leading to better decision support.
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