Artificial intelligence model trained to predict and detect intraoperative seizures during brain surgery
Full Description
We aim to design a Multi-Modal Deep Learning Transformer to detect seizures earlier than is currently achieved in brain surgeries. We will train our transformer with intraoperative neuromonitoring data from past cranial surgeries, which it will use to predict probability of seizure onset. We will then use a novel mixed reality headset application to present the detected seizure probabilities to users in real time.