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Trajectory Inspection: A Method for Iterative Clinician-Driven Design of
  Reinforcement Learning Studies
v1v2 (latest)

Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies

8 October 2020
Christina X. Ji
Michael Oberst
S. Kanjilal
David Sontag
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies"

4 / 4 papers shown
Title
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
135
0
0
25 Nov 2025
medDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support
medDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support
Qianyi Xu
Gousia Habib
Dilruk Perera
Mengling Feng
Mengling Feng
OffRL
298
1
0
26 May 2025
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
108
0
0
10 Apr 2024
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety
  Constraints in Finite MDPs
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPsNeural Information Processing Systems (NeurIPS), 2021
Harsh Satija
Philip S. Thomas
Joelle Pineau
Romain Laroche
OffRL
219
26
0
31 May 2021
1