Closed-loop control of anesthesia and mean arterial pressure using reinforcement learning

By Regina Padmanabhan, Nader Meskin, Wassim M. Haddad. 2014

106 citations recorded by the source corpus.

Subfields: Anesthesiology and Pain Medicine, Critical Care and Intensive Care Medicine, Developmental Neuroscience

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Anesthesiology and Pain Medicine

1. Shamim Nemati
2. Chao Yu
3. Jiming Liu

In Critical Care and Intensive Care Medicine

1. Shamim Nemati
2. Jiming Liu
3. Chao Yu

In Developmental Neuroscience

1. Shamim Nemati
2. Chao Yu
3. Jiming Liu

Citations in the corpus

• Reinforcement Learning in Healthcare: A Survey (2019, methodology): “under sedation can cause symptoms such as anxiety, agitation and hyperoxia [213].”
• Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units (2019, background): “…learning (RL) [1] has achieved tremendous achievements in solving complex sequential decision making problems in various health care domains, including treatment in HIV [2], cancer [3], diabetics [4], anaemia [5], schizophrenia [6], epilepsy [7], anesthesia [8], and sepsis [9], just to name a few.”