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Opportunities and possibilities of outcome prediction in patients who will undergo a transcatheter aortic valve procedure : a data-driven approach

Schaft, E.V. (2019) Opportunities and possibilities of outcome prediction in patients who will undergo a transcatheter aortic valve procedure : a data-driven approach.

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Abstract:Patients with an aortic stenosis who have a high risk for undergoing surgery, can get a transcatheter aortic valve implantation (TAVI). In this project machine learning techniques are used to evaluate what the opportunities and possibilities are to predict the outcome of patients who will undergo a TAVI. It is shown that electrocardiography and convolutional neural networks are able to predict the improvement of shortness of breath after a TAVI. Also, the steps to implement a data-driven model in the daily clinical practice are elaborated.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 44 medicine
Programme:Applied Mathematics MSc (60348)
Link to this item:https://purl.utwente.nl/essays/80167
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