EEG based outcome prediction with artificial intelligence for patients in coma after cardiac arrest
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In this feasibility study we will explore the market potential for software that applies Artificial Intelligence (AI)-driven prediction models to EEG data for patients in post-anoxic coma in the Intensive Care Unit (ICU). EEG is a powerful tool for outcome prediction in these patients, yet current visual analysis methods and full EEG interpretation are highly labor-intensive. By automating this process with AI, we seek to improve efficiency and accessibility of prognostic assessments. This study will assess the commercial feasibility and potential adoption of such software in clinical practice.
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