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Early detection of positive blood cultures using recurrent neural networks on time series data

Thomas Peiffer, Joeri Ruyssinck (UGent) , Johan Decruyenaere (UGent) , Filip De Turck (UGent) , Femke Ongenae (UGent) and Tom Dhaene (UGent)
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The ignition of supernova explosions and neutrino nucleo synthesis.

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Please use this url to cite or link to this publication:

Chicago
Peiffer, Thomas, Joeri Ruyssinck, Johan Decruyenaere, Filip De Turck, Femke Ongenae, and Tom Dhaene. 2016. “Early Detection of Positive Blood Cultures Using Recurrent Neural Networks on Time Series Data.” In Proceedings of Benelearn 2016.
APA
Peiffer, T., Ruyssinck, J., Decruyenaere, J., De Turck, F., Ongenae, F., & Dhaene, T. (2016). Early detection of positive blood cultures using recurrent neural networks on time series data. Proceedings of Benelearn 2016. Presented at the 25th Belgian-Dutch conference on Machine Learning (BeneLearn 2016).
Vancouver
1.
Peiffer T, Ruyssinck J, Decruyenaere J, De Turck F, Ongenae F, Dhaene T. Early detection of positive blood cultures using recurrent neural networks on time series data. Proceedings of Benelearn 2016. 2016.
MLA
Peiffer, Thomas et al. “Early Detection of Positive Blood Cultures Using Recurrent Neural Networks on Time Series Data.” Proceedings of Benelearn 2016. 2016. Print.
@inproceedings{8606679,
  author       = {Peiffer, Thomas and Ruyssinck, Joeri and Decruyenaere, Johan and De Turck, Filip and Ongenae, Femke and Dhaene, Tom},
  booktitle    = {Proceedings of Benelearn 2016},
  language     = {eng},
  location     = {Kortrijk, Belgium},
  pages        = {3},
  title        = {Early detection of positive blood cultures using recurrent neural networks on time series data},
  url          = {https://www.kuleuven-kulak.be/benelearn/papers/Benelearn\_2016\_paper\_30.pdf},
  year         = {2016},
}