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Does the "Artificial Intelligence Clinician" learn optimal treatment
  strategies for sepsis in intensive care?

Does the "Artificial Intelligence Clinician" learn optimal treatment strategies for sepsis in intensive care?

8 February 2019
R. Bradford
C. Sangwin
S. Shashikumar
S. Nemati
    OOD
ArXiv (abs)PDFHTML

Papers citing "Does the "Artificial Intelligence Clinician" learn optimal treatment strategies for sepsis in intensive care?"

10 / 10 papers shown
Exploring Time-Step Size in Reinforcement Learning for Sepsis Treatment
Exploring Time-Step Size in Reinforcement Learning for Sepsis Treatment
Yingchuan Sun
Shengpu Tang
OffRL
216
1
0
25 Nov 2025
Offline Inverse Constrained Reinforcement Learning for Safe-Critical
  Decision Making in Healthcare
Offline Inverse Constrained Reinforcement Learning for Safe-Critical Decision Making in HealthcareIEEE Transactions on Artificial Intelligence (IEEE TAI), 2024
Nan Fang
Guiliang Liu
Wei Gong
OffRL
356
5
0
10 Oct 2024
Reinforcement Learning in Dynamic Treatment Regimes Needs Critical
  Reexamination
Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
Zhiyao Luo
Yangchen Pan
Peter Watkinson
Tingting Zhu
OffRL
281
4
0
28 May 2024
How Consistent are Clinicians? Evaluating the Predictability of Sepsis
  Disease Progression with Dynamics Models
How Consistent are Clinicians? Evaluating the Predictability of Sepsis Disease Progression with Dynamics Models
Unnseo Park
Venkatesh Sivaraman
Adam Perer
164
2
0
10 Apr 2024
Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of
  AI-Based Treatment Recommendations in Health Care
Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health CareInternational Conference on Human Factors in Computing Systems (CHI), 2023
Venkatesh Sivaraman
L. Bukowski
J. Levin
J. Kahn
Adam Perer
371
138
0
31 Jan 2023
Trajectory Inspection: A Method for Iterative Clinician-Driven Design of
  Reinforcement Learning Studies
Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies
Christina X. Ji
Michael Oberst
S. Kanjilal
David Sontag
OffRL
259
9
0
08 Oct 2020
Missingness as Stability: Understanding the Structure of Missingness in
  Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
Scott L. Fleming
Kuhan Jeyapragasan
Tony Duan
D. Ding
S. Gombar
N. Shah
Emma Brunskill
OOD
158
3
0
16 Nov 2019
Reinforcement Learning in Healthcare: A Survey
Reinforcement Learning in Healthcare: A SurveyACM Computing Surveys (ACM CSUR), 2019
Chao Yu
Jiming Liu
S. Nemati
LM&MAOffRL
801
733
0
22 Aug 2019
Inverse Reinforcement Learning in Contextual MDPs
Inverse Reinforcement Learning in Contextual MDPs
Stav Belogolovsky
Philip Korsunsky
Shie Mannor
Chen Tessler
Tom Zahavy
OffRLBDL
442
19
0
23 May 2019
Understanding the Artificial Intelligence Clinician and optimal
  treatment strategies for sepsis in intensive care
Understanding the Artificial Intelligence Clinician and optimal treatment strategies for sepsis in intensive care
Matthieu Komorowski
Leo Anthony Celi
Omar Badawi
A. Gordon
A. Faisal
120
6
0
06 Mar 2019
1
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