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
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
Guidelines for reinforcement learning in healthcare
O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, ...
Nature medicine 25 (1), 16-18, 2019
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ...
bmj 377, 2022
Continuous state-space models for optimal sepsis treatment: a deep reinforcement learning approach
A Raghu, M Komorowski, LA Celi, P Szolovits, M Ghassemi
Machine Learning for Healthcare Conference, 147-163, 2017
Reprint of: Air travel and COVID-19 prevention in the pandemic and peri-pandemic period: A narrative review
M Bielecki, D Patel, J Hinkelbein, M Komorowski, J Kester, S Ebrahim, ...
Travel medicine and infectious disease 38, 101939, 2020
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
Exploratory data analysis
MITC Data, M Komorowski, DC Marshall, JD Salciccioli, Y Crutain
Secondary analysis of electronic health records, 185-203, 2016
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
Improving sepsis treatment strategies by combining deep and kernel-based reinforcement learning
X Peng, Y Ding, D Wihl, O Gottesman, M Komorowski, HL Li-wei, A Ross, ...
AMIA Annual Symposium Proceedings 2018, 887, 2018
Markov models and cost effectiveness analysis: applications in medical research
MITC Data, M Komorowski, J Raffa
Secondary analysis of electronic health records, 351-367, 2016
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 31, 2018
Sensitivity analysis and model validation
MITC Data, JD Salciccioli, Y Crutain, M Komorowski, DC Marshall
Secondary analysis of electronic health records, 263-271, 2016
Artificial intelligence in intensive care: are we there yet?
M Komorowski
Intensive care medicine 45 (9), 1298-1300, 2019
Secondary analysis of electronic health records
M Komorowski, DC Marshall, JD Salciccioli, Y Crutain
Second. Anal. Electron. Heal. Rec, 1-427, 2016
Interdisciplinary research in artificial intelligence: challenges and opportunities
R Kusters, D Misevic, H Berry, A Cully, Y Le Cunff, L Dandoy, ...
Frontiers in big data 3, 577974, 2020
Implications of obesity for the management of severe coronavirus disease 2019 pneumonia
M Lemyze, N Courageux, T Maladobry, C Arumadura, P Pauquet, A Orfi, ...
Critical Care Medicine 48 (9), e761-e767, 2020
Natural history, trajectory, and management of mechanically ventilated COVID-19 patients in the United Kingdom
BV Patel, S Haar, R Handslip, C Auepanwiriyakul, TML Lee, S Patel, ...
Intensive care medicine 47 (5), 549-565, 2021
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, 1-9, 2018
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