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Multiple Instance Learning for Brain Tumor Detection from Magnetic Resonance Spectroscopy Data
Specifically, we aggregate multiple spectra from the same patient into a "bag" for classification and apply data augmentation techniques.
Staging Epileptogenesis with Deep Neural Networks
Specifically, continuous intracranial EEG recordings were collected from a rodent model where epilepsy is induced by electrical perforant pathway stimulation (PPS).
Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation
The application of Deep Learning (DL) for medical diagnosis is often hampered by two problems.
Towards Early Diagnosis of Epilepsy from EEG Data
This demonstrates the feasibility of EPG prediction from EEG recordings.
Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy
We conclude that modern deep learning approaches can reach state-of-the-art performance on epileptic EEG classification and automated seizure onset zone identification tasks when trained on raw EEG data.
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