Imperial College London

Professor Anthony Gordon

Faculty of MedicineDepartment of Surgery & Cancer

Chair in Anaesthesia and Critical Care
 
 
 
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Contact

 

+44 (0)20 3312 6328anthony.gordon

 
 
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Location

 

ICUQueen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Komorowski:2019,
author = {Komorowski, M and Celi, LA and Badawi, O and Gordon, AC and Faisal, AA},
title = {Understanding the artificial intelligence clinician and optimal treatment strategies for sepsis in intensive care},
url = {http://arxiv.org/abs/1903.02345v1},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - UNPB
AB - In this document, we explore in more detail our published work (Komorowski,Celi, Badawi, Gordon, & Faisal, 2018) for the benefit of the AI in Healthcareresearch community. In the above paper, we developed the AI Clinician system,which demonstrated how reinforcement learning could be used to make usefulrecommendations towards optimal treatment decisions from intensive care data.Since publication a number of authors have reviewed our work (e.g. Abbasi,2018; Bos, Azoulay, & Martin-Loeches, 2019; Saria, 2018). Given the differenceof our framework to previous work, the fact that we are bridging two verydifferent academic communities (intensive care and machine learning) and thatour work has impact on a number of other areas with more traditionalcomputer-based approaches (biosignal processing and control, biomedicalengineering), we are providing here additional details on our recentpublication.
AU - Komorowski,M
AU - Celi,LA
AU - Badawi,O
AU - Gordon,AC
AU - Faisal,AA
PY - 2019///
TI - Understanding the artificial intelligence clinician and optimal treatment strategies for sepsis in intensive care
UR - http://arxiv.org/abs/1903.02345v1
UR - http://hdl.handle.net/10044/1/71475
ER -