Matthieu Komorowski

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A. Aldo FaisalProfessor in AI & Neuroscience, Imperial College; Chair in Digital Health, University of BayreuthVerified email at imperial.ac.uk
Anthony GordonProfessor, Imperial College LondonVerified email at imperial.ac.uk
Leo Anthony CeliMassachusetts Institute of TechnologyVerified email at mit.edu
Myura NagendranUKRI Clinical PhD Fellow, Centre for AI in Healthcare, Imperial College LondonVerified email at imperial.ac.uk
Dominic C MarshallImperial College LondonVerified email at imperial.ac.uk
Justin D SalciccioliBrigham and Women's Hospital - Harvard Medical SchoolVerified email at bwh.harvard.edu
Omer GottesmanAmazonVerified email at amazon.com
Finale Doshi-VelezProfessor, HarvardVerified email at seas.harvard.edu
Aniruddh RaghuMITVerified email at mit.edu
Omar Badawi, PharmD, MPH, FCCMUS Army Telemedicine and Advanced Technology Research CenterVerified email at health.mil
Paul FestorPhD student, Imperial College LondonVerified email at imperial.ac.uk
PD Dr. med. Christopher Neuhaus, M....Universitätsklinikum HeidelbergVerified email at med.uni-heidelberg.de
Gary S. CollinsProfessor of Medical Statistics, Centre for Statistics in Medicine, University of OxfordVerified email at csm.ox.ac.uk
Ibrahim HabliProfessor of Safety-Critical Systems at the University of YorkVerified email at york.ac.uk
Fredrik D. JohanssonAssociate Professor, Chalmers University of TechnologyVerified email at chalmers.se
David SontagProfessor, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Dr. Marzyeh GhassemiAssociate Professor, EECS/IMES, MITVerified email at mit.edu
Peter SzolovitsProfessor of Computer Science and Engineering, MITVerified email at mit.edu
Li-wei H. LehmanMassachusetts Institute of TechnologyVerified email at mit.edu
Eric TopolProfessor and EVP, Scripps ResearchVerified email at scripps.edu

Matthieu Komorowski

MD, PhD, Clinical Senior Lecturer at Imperial College London ; Visiting Scholar at MIT

Verified email at imperial.ac.uk - Homepage

Anesthesia Critical Care Machine Learning Space Medicine


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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	1049	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	788	2020
Guidelines for reinforcement learning in healthcare O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, ... Nature medicine 25 (1), 16-18, 2019	461	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	333	2022
Secondary Analysis of Electronic Health Records MITC Data Springer International Publishing, 2016	278*	2016
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	239	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	221	2020
Deep reinforcement learning for sepsis treatment A Raghu, M Komorowski, I Ahmed, L Celi, P Szolovits, M Ghassemi arXiv preprint arXiv:1711.09602, 2017	218	2017
Exploratory data analysis MITC Data, M Komorowski, DC Marshall, JD Salciccioli, Y Crutain Secondary analysis of electronic health records, 185-203, 2016	217	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	130	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	101	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	85	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	79	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	79	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	70	2020
Artificial intelligence in intensive care: are we there yet? M Komorowski Intensive care medicine 45 (9), 1298-1300, 2019	64	2019
Sepsis biomarkers and diagnostic tools with a focus on machine learning M Komorowski, A Green, KC Tatham, C Seymour, D Antcliffe EBioMedicine 86, 2022	60	2022
Secondary analysis of electronic health records M Komorowski, DC Marshall, JD Salciccioli, Y Crutain Second. Anal. Electron. Heal. Rec, 1-427, 2016	59	2016
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	57	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	56	2018

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