Matthieu Komorowski
Matthieu Komorowski
MD, PhD, Clinical Senior Lecturer at Imperial College London ; Visiting Scholar at MIT
Verified email at - Homepage
Cited by
Cited by
The artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care
M Komorowski, LA Celi, O Badawi, AC Gordon, AA Faisal
Nature medicine 24 (11), 1716-1720, 2018
Continuous state-space models for optimal sepsis treatment-a deep reinforcement learning approach
A Raghu, M Komorowski, LA Celi, P Szolovits, M Ghassemi
arXiv preprint arXiv:1705.08422, 2017
Guidelines for reinforcement learning in healthcare
O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, ...
Nat Med 25 (1), 16-18, 2019
Secondary Analysis of Electronic Health Records
Springer International Publishing, 2016
Deep reinforcement learning for sepsis treatment
A Raghu, M Komorowski, I Ahmed, L Celi, P Szolovits, M Ghassemi
arXiv preprint arXiv:1711.09602, 2017
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies
M Nagendran, Y Chen, CA Lovejoy, AC Gordon, M Komorowski, ...
bmj 368, 2020
Representation balancing mdps for off-policy policy evaluation
Y Liu, O Gottesman, A Raghu, M Komorowski, AA Faisal, F Doshi-Velez, ...
Advances in Neural Information Processing Systems, 2644-2653, 2018
Evaluating reinforcement learning algorithms in observational health settings
O Gottesman, F Johansson, J Meier, J Dent, D Lee, S Srinivasan, L Zhang, ...
arXiv preprint arXiv:1805.12298, 2018
Potential anesthesia protocols for space exploration missions
M Komorowski, SD Watkins, G Lebuffe, JB Clark
Aviation, space, and environmental medicine 84 (3), 226-233, 2013
Trends in mortality from pneumonia in the Europe union: a temporal analysis of the European detailed mortality database between 2001 and 2014
DC Marshall, RJ Goodson, Y Xu, M Komorowski, J Shalhoub, ...
Respiratory research 19 (1), 81, 2018
Improving sepsis treatment strategies by combining deep and kernel-based reinforcement learning
X Peng, Y Ding, D Wihl, O Gottesman, M Komorowski, LH Lehman, ...
AMIA Annual Symposium Proceedings 2018, 887, 2018
Fundamentals of anesthesiology for spaceflight
M Komorowski, S Fleming, AW Kirkpatrick
J Cardiothorac Vasc Anesth 30 (3), 781-790, 2016
Bridging the health data divide
LA Celi, G Davidzon, AEW Johnson, M Komorowski, DC Marshall, ...
Journal of Medical Internet Research 18 (12), e325, 2016
Markov models and cost effectiveness analysis: applications in medical research
M Komorowski, J Raffa
Secondary analysis of electronic health records, 351-367, 2016
Exploratory data analysis
M Komorowski, DC Marshall, JD Salciccioli, Y Crutain
Secondary Analysis of Electronic Health Records, 185-203, 2016
Intubation after rapid sequence induction performed by non-medical personnel during space exploration missions: a simulation pilot study in a Mars analogue environment
M Komorowski, S Fleming
Extreme physiology & medicine 4 (1), 19, 2015
Behaviour policy estimation in off-policy policy evaluation: Calibration matters
A Raghu, O Gottesman, Y Liu, M Komorowski, A Faisal, F Doshi-Velez, ...
arXiv preprint arXiv:1807.01066, 2018
Anaesthesia in austere environments: literature review and considerations for future space exploration missions
M Komorowski, S Fleming, M Mawkin, J Hinkelbein
NPJ microgravity 4 (1), 1-11, 2018
A Markov Decision Process to suggest optimal treatment of severe infections in intensive care
M Komorowski, A Gordon, LA Celi, A Faisal
Neural Information Processing Systems Workshop on Machine Learning for Health, 2016
Model-based reinforcement learning for sepsis treatment
A Raghu, M Komorowski, S Singh
arXiv preprint arXiv:1811.09602, 2018
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