DAAL: A Deep Aggregated Assemble Learning Model for detecting Epileptic patients from EEG
- Resource Type
- Conference
- Authors
- Parui, Sricheta; Ghosh, Uttam; Chatterjee, Puspita; Basu, Deborsi
- Source
- 2022 IEEE 4th PhD Colloquium on Emerging Domain Innovation and Technology for Society (PhD EDITS) PhD Colloquium on Emerging Domain Innovation and Technology for Society (PhD EDITS), 2022 IEEE 4th. :1-2 Nov, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Technological innovation
Merging
Epilepsy
Predictive models
Brain modeling
Prediction algorithms
Neural Network
CNN
RNN
ANN
EEG
- Language
In this study, we developed a Deep Aggregated Assemble Learning(DAAL) model to diagnose Epilepsy that uses two-step learning and generates the final prediction utilizing the output predictions of the level 0 classifier model. In level 0 CNN, RNN and ANN model has been used, and then a prediction algorithm has been used which predicts the final output from each of the probability vector coming from each model.