A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features

A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features

<italic>Goal:</italic> The purpose of this study is to evaluate the importance of cardiorespiratory variables within a Reinforcement Learning (RL) recommendation system aimed at establishing optimal strategies for drug treatment of septic patients in the intensive care unit (ICU). <it...

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Bibliographic Details
Main Authors: Cristian Drudi, Maximiliano Mollura, Li-wei H. Lehman, Riccardo Barbieri
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of Engineering in Medicine and Biology
Subjects:
Cardiovascular system
dimensionality reduction
intensive care unit
reinforcement learning
sepsis
Online Access:https://ieeexplore.ieee.org/document/10439998/
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