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Results: 5
Number of items: 5
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Dam, T. A., Hoogendoorn, M., Elbers, P. W. G., & Dutch ICU Data Sharing Against COVID-19 Collaborators (2022). Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning. Annals of intensive care, 12, Article 99. https://doi.org/10.1186/s13613-022-01070-0 -
Fleuren, L. M., Fornasa, M., Cinà, G., Hoogendoorn, M., Elbers, P. W. G., & Dutch ICU Data Sharing Against COVID-19 Collaborators (2021). Predictors for extubation failure in COVID-19 patients using a machine learning approach. Critical Care, 25, Article 448. https://doi.org/10.1186/s13054-021-03864-3
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Romero, D. W., Kuzina, A., Bekkers, E. J., Tomczak, J. M., & Hoogendoorn, M. (2021). CKConv: Continuous Kernel Convolution For Sequential Data. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2102.02611
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Romero, D. W., Bekkers, E. J., Tomczak, J. M., & Hoogendoorn, M. (2020). Wavelet networks: Scale equivariant learning from raw waveforms. (v1 ed.) ArXiv. https://arxiv.org/abs/2006.05259
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Romero, D. W., Bekkers, E. J., Tomczak, J. M., & Hoogendoorn, M. (2020). Attentive group equivariant convolutional networks. Proceedings of Machine Learning Research, 119, 8188-8199. http://proceedings.mlr.press/v119/romero20a.html
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