Oct 28, 2021 · In this work, we focus on recovering clinicians' rewards in treating patients. We incorporate the what-if reasoning to explain the clinician's treatments.
Oct 26, 2022 · TL;DR: We recover clinicians' goals of treatments by integrating counterfactual reasoning into batch inverse reinforcement learning and ...
Oct 28, 2021 · We incorporate the what-if reasoning to explain clinician's actions based on future outcomes. We use generalized additive models (GAMs) – a ...
Sep 7, 2024 · We incorporate the what-if reasoning to explain clinician's actions based on future outcomes. We use generalized additive models (GAMs) - a ...
In this work, we focus on recovering clinicians' rewards in treating patients. We incorporate the what-if reasoning to explain clinician's actions based on ...
We incorporate the what-if reasoning to explain clinician's actions based on future outcomes. We use generalized additive models (GAMs) - a class of accurate, ...
Extracting Expert's Goals by What-if Interpretable Modeling
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Oct 28, 2021 · This work uses generalized additive models (GAMs) - a class of accurate, interpretable models - to recover clinicians' rewards in treating ...
Oct 28, 2021 · Extracting Clinician's Goals by What-if Interpretable Modeling. 1−3Chun-Hao Chang 1−3George Alexandru Adam. 4Rich Caruana. 1−3Anna ...
In this work, we focus on understanding the motivations for clinicians managing hypotension in the ICU. We model the ICU interventions as a batch, sequential ...
Extracting Clinician's Goals by What-if Interpretable Modeling. CH Chang, GA Adam, R Caruana, A Goldenberg. CoRR, 2021. 2021. The system can't perform the ...