Követés
Matthieu Komorowski
Matthieu Komorowski
MD, PhD, Clinical Senior Lecturer at Imperial College London ; Visiting Scholar at MIT
E-mail megerősítve itt: imperial.ac.uk - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
11932018
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
8732020
Guidelines for reinforcement learning in healthcare
O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, ...
Nature medicine 25 (1), 16-18, 2019
4942019
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
4232022
Secondary Analysis of Electronic Health Records
MITC Data
Springer International Publishing, 2016
289*2016
Exploratory data analysis
MITC Data, M Komorowski, DC Marshall, JD Salciccioli, Y Crutain
Secondary analysis of electronic health records, 185-203, 2016
2712016
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
2602017
Deep reinforcement learning for sepsis treatment
A Raghu, M Komorowski, I Ahmed, L Celi, P Szolovits, M Ghassemi
arXiv preprint arXiv:1711.09602, 2017
2442017
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
2432020
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
1472018
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
1172018
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
992020
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
962016
Sensitivity analysis and model validation
MITC Data, JD Salciccioli, Y Crutain, M Komorowski, DC Marshall
Secondary analysis of electronic health records, 263-271, 2016
912016
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
852018
Sepsis biomarkers and diagnostic tools with a focus on machine learning
M Komorowski, A Green, KC Tatham, C Seymour, D Antcliffe
EBioMedicine 86, 2022
792022
Secondary analysis of electronic health records
M Komorowski, DC Marshall, JD Salciccioli, Y Crutain
Second. Anal. Electron. Heal. Rec., no. September, 1-427, 2016
682016
Model-based reinforcement learning for sepsis treatment
A Raghu, M Komorowski, S Singh
arXiv preprint arXiv:1811.09602, 2018
642018
Artificial intelligence in intensive care: are we there yet?
M Komorowski
Intensive care medicine 45 (9), 1298-1300, 2019
632019
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
592021
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