Outcome prediction for endovascular therapy: Multimodal deep learning for acute ischemic events in the arteria cerebri media

The efficacy of endovascular therapy in large vessel occlusion (LVO) of the anterior circulation is dependent to a high degree on the selection of patients who are likely to benefit from this procedure. To this end, functional outcome prediction based on clinical parameters is an active area of research. In the preoperative screening of LVO...

Towards Natural Language Understanding using Multimodal Deep Learning

This thesis describes how multimodal sensor data from a 3D sensor and microphone array can be processed with deep neural networks such that its fusion, the trained neural network, is a) more robust to noise, b) outperforms unimodal recognition and c) enhances unimodal recognition in absence of multimodal data. We built a framework for a complete...