Multimodal deep learning approach to predicting neurological recovery from coma after cardiac arrest
This work showcases our team's (The BEEGees) contributions to the 2023 George B. Moody PhysioNet Challenge. The aim was to predict neurological recovery from coma following cardiac arrest using clinical data and time-series such as multi-channel EEG and ECG signals. Our modelling approach is mu...
| Huvudupphovsmän: | , , , , |
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| Materialtyp: | Conference item |
| Språk: | English |
| Publicerad: |
IEEE
2023
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