| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |
|---|---|---|---|---|---|---|
| 2 | Grover N., Chharia A., Upadhyay R., Longo L. | Schizo-Net: A novel Schizophrenia Diagnosis framework using late fusion multimodal deep learning on Electroencephalogram-based Brain connectivity indices | IEEE Transactions on Neural Systems and Rehabilitation Engineering | 2023 |  
| Schizophrenia • Deep Learning • Brain Connectivity features • Feature fusion • Classification • Machine Learning |
| 1 | Jindala K., Upadhyaya R., Padhyb P.K., Longo L. | Bi-LSTM-deep CNN for schizophrenia detection using MSST-spectral images of EEG signals | Artificial Intelligence-Based Brain-Computer Interface | 2022 | 
@incollection{JINDAL2022145, title = {6 - Bi-LSTM-deep CNN for schizophrenia detection using MSST-spectral images of EEG signals}, editor = {Varun Bajaj and G.R. Sinha}, booktitle = {Artificial Intelligence-Based Brain-Computer Interface}, publisher = {Academic Press}, pages = {145-162}, year = {2022}, isbn = {978-0-323-91197-9}, doi = {https://doi.org/10.1016/B978-0-323-91197-9.00011-4}, url = {https://www.sciencedirect.com/science/article/pii/B9780323911979000114}, author = {Komal Jindal and Rahul Upadhyay and Prabin Kumar Padhy and Luca Longo}, keywords = {Schizophrenia, Electroencephalography, Multisynchrosqueezing transform, Bi-directional long short-term memory, Convolutional neural network, Classification, Deep learning} } [Close]
| bi-directional LSTM • Long-Short Term Memory • Deep Learning • Schizophrenia • Spectral analysis • Convolutional neural network • Electroencephalography |
| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |