The artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care
Sepsis is the third leading cause of death worldwide and the main cause of mortality in
hospitals,–, but the best treatment strategy remains uncertain. In particular, evidence …
hospitals,–, but the best treatment strategy remains uncertain. In particular, evidence …
Individualized sepsis treatment using reinforcement learning
S Saria - Nature medicine, 2018 - nature.com
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Clinical management of sepsis can be improved by artificial intelligence: yes
M Komorowski - Intensive care medicine, 2020 - Springer
The management of sepsis is a highly complex, multifaceted challenge that remains the
realm of highly skilled and trained human experts. But as medical applications of artificial …
realm of highly skilled and trained human experts. But as medical applications of artificial …
Deep reinforcement learning for sepsis treatment
Sepsis is a leading cause of mortality in intensive care units and costs hospitals billions
annually. Treating a septic patient is highly challenging, because individual patients …
annually. Treating a septic patient is highly challenging, because individual patients …
Continuous state-space models for optimal sepsis treatment: a deep reinforcement learning approach
Sepsis is a leading cause of mortality in intensive care units (ICUs) and costs hospitals
billions annually. Treating a septic patient is highly challenging, because individual patients …
billions annually. Treating a septic patient is highly challenging, because individual patients …
[HTML][HTML] Improving sepsis treatment strategies by combining deep and kernel-based reinforcement learning
Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because
individual patients respond differently to treatment. Thus, tailoring treatment to the individual …
individual patients respond differently to treatment. Thus, tailoring treatment to the individual …
Ignore, trust, or negotiate: understanding clinician acceptance of AI-based treatment recommendations in health care
Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but
clinician acceptance remains a critical barrier. We developed a novel decision support …
clinician acceptance remains a critical barrier. We developed a novel decision support …
Deep reinforcement learning and simulation as a path toward precision medicine
Traditionally, precision medicine involves classifying patients to identify subpopulations that
respond favorably to specific therapeutics. We pose precision medicine as a dynamic …
respond favorably to specific therapeutics. We pose precision medicine as a dynamic …
A value-based deep reinforcement learning model with human expertise in optimal treatment of sepsis
XD Wu, RC Li, Z He, TZ Yu, CQ Cheng - NPJ Digital Medicine, 2023 - nature.com
Abstract Deep Reinforcement Learning (DRL) has been increasingly attempted in assisting
clinicians for real-time treatment of sepsis. While a value function quantifies the performance …
clinicians for real-time treatment of sepsis. While a value function quantifies the performance …
Deep inverse reinforcement learning for sepsis treatment
C Yu, G Ren, J Liu - 2019 IEEE international conference on …, 2019 - ieeexplore.ieee.org
Sepsis is a leading cause of mortality in hospitals, but its optimal treatment strategy still
remains unclear. Recent years have witnessed several successful applications of …
remains unclear. Recent years have witnessed several successful applications of …