Ensemble Learning Using Individual Neonatal Data for Seizure Detection-Reference-Cited by-同舟云学术

Ensemble Learning Using Individual Neonatal Data for Seizure Detection

Published:2022 Issue: Volume:10 Page:1-11
ISSN:2168-2372
Container-title:IEEE Journal of Translational Engineering in Health and Medicine
language:
Short-container-title:IEEE J. Transl. Eng. Health Med.

Author:

Borovac Ana¹^ORCID,Gudmundsson Steinn¹,Thorvardsson Gardar²,Moghadam Saeed M.³,Nevalainen Paivi³,Stevenson Nathan⁴,Vanhatalo Sampsa³,Runarsson Thomas P.¹

Affiliation:

1. Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavik, Iceland

2. Kvikna Medical ehf., Reykjavik, Iceland

3. Department of Physiology, BABA Center, Pediatric Research Center, University of Helsinki, Helsinki, Finland

4. Brain Modelling Group, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia

Funder

Sigrid Juselius Foundation

European Union’s Horizon 2020 Research and Innovation Programme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Medicine

Link

http://xplorestaging.ieee.org/ielx7/6221039/9652399/09864642.pdf?arnumber=9864642

Reference56 articles.

1. Review of Neonatal EEG

2. A dataset of neonatal EEG recordings with seizure annotations;stevenson;Data Science Journal,2019

3. Convolutional neural networks ensemble model for neonatal seizure detection

4. AEEG signal analysis with ensemble learning for newborn seizure detection;pan;Proc Int Workshop Multiscale Multimodal Med Imag,2019

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