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Sepsis is a dangerous condition that is a leading cause of patient mortality.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Tree-based batch mode reinforcement learning
Damien Ernst, Pierre Geurts, and Louis Wehenkel · 2005
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Sepsis: a roadmap for future research
J. Cohen, J.-L. Vincent, N. K. J. Adhikari, F. R. Machado, D. C. Angus, T. Calandra, K. Jaton, S. Giulieri, J.Delaloye, S. Opal, K. Tracey, T. van der Poll, and E. Pelfrene · 2006
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Sepsis in European intensive care units: results of the SOAP study
J.-L. Vincent, Y. Sakr, C. L. Sprung, V. M. Ranieri, K. Reinhart, H. Gerlach, R. Moreno, J. Carlet, J.-R. Le Gall, and D. Payen · 2006
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Interaction between fluids and vasoactive agents on mortality in septic shock: a multicenter, observational study
Jason Waechter, Anand Kumar, Stephen E Lapinsky, John Marshall, Peter Dodek, Yaseen Arabi, Joseph E Parrillo, R Phillip Dellinger, Allan Garland, and Cooperative Antimicrobial Therapy of Septic Shock Database Research Group and others · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Learning and policy search in stochastic dynamical systems with Bayesian neural networks
Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez, and Steffen Udluft · 2016
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Black-box alpha divergence minimization
Jose Hernandez-Lobato, Yingzhen Li, Mark Rowland, Thang Bui, Daniel Hernandez-Lobato, and Richard Turner · 2016
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MIMIC-III, a freely accessible critical care database
A. E. W. Johnson, T. J. Pollard, L. Shen, L.-W. H. Lehman, M. Feng, M. Ghassemi, B. Moody, P. Szolovits, L. Anthony Celi, and R. G. Mark · 2016
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A Markov Decision Process to suggest optimal treatment of severe infections in intensive care
M. Komorowski, A. Gordon, L. A. Celi, and A. Faisal · 2016
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Surviving sepsis campaign: International guidelines for management of sepsis and septic shock: 2016
Andrew Rhodes, Laura E Evans, Waleed Alhazzani, Mitchell M Levy, Massimo Antonelli, Ricard Ferrer, Anand Kumar, Jonathan E Sevransky, Charles L Sprung, Mark E Nunnally, et al · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Evaluating reinforcement learning algorithms in observational health settings
Omer Gottesman, Fredrik Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, et al · 2018
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Representation balancing mdps for off-policy policy evaluation
Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, and Emma Brunskill · 2018
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The third international consensus definitions for sepsis and septic shock (sepsis-3)
M. Singer, C. S. Deutschman, C. Seymour, et al · 2016
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Neural network dynamics for model-based deep reinforcement learning with model-free fine-tuning
Anusha Nagabandi, Gregory Kahn, Ronald S Fearing, and Sergey Levine · 2017
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Deep reinforcement learning for sepsis treatment
Aniruddh Raghu, Matthieu Komorowski, Imran Ahmed, Leo Celi, Peter Szolovits, and Marzyeh Ghassemi
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Continuous state-space models for optimal sepsis treatment: a deep reinforcement learning approach
Aniruddh Raghu, Matthieu Komorowski, Leo Anthony Celi, Peter Szolovits, and Marzyeh Ghassemi
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Dougal Maclaurin, David Duvenaud, and Matthew Johnson · 2018
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Behaviour policy estimation in off-policy policy evaluation: Calibration matters
Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, and Emma Brunskill · 2018
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