Early Detection of Sepsis Using LSTM and Reinforcement Learning

Author:

Dhanalakshmi R.,Sudalaimuthu T.,Radhakrishnan K. R.

Publisher

Springer Nature Singapore

Reference17 articles.

1. Futoma J et al (2017) Learning to detect sepsis with a multitask Gaussian process RNN classifier. In: International conference on machine learning, pp 1174–1182

2. Lea C et al (2017) Temporal convolutional networks for action segmentation and detection. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 1003–1012

3. Fagerström J, Bång M, Wilhelms D, Chew MS (2019) LiSep LSTM: a machine learning algorithm for early detection of septic shock. Sci Rep 9. Article No. 15132

4. Lauritsen SM, Kalør ME, Kongsgaard EL, Lauritsen KM, Jørgensen MJ, Lange J, Thiesson B (2019) Early detection of sepsis utilizing deep learning on electronic health record event sequences. Artif Intell Med arXiv:1906.02956v1

5. Moor M, Horn M, Rieck B, Roqueiro D, Borgwardt K (2019) Early recognition of sepsis with Gaussian process temporal convolutional networks and dynamic time warping. In: Proceedings of machine learning research, vol 106, pp 1–IX

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