A Transformer-Based Prediction Method for Depth of Anesthesia During Target-Controlled Infusion of Propofol and Remifentanil
Author:
Affiliation:
1. School of Information Engineering, Guangdong University of Technology, Guangzhou, China
2. Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine, Baoshan, China
Funder
Guangdong Basic and Applied Basic Research Foundation
Guangdong Provincial Key Laboratory of Intellectual Property and Big Data
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation
Link
http://xplorestaging.ieee.org/ielx7/7333/10031624/10218321.pdf?arnumber=10218321
Reference32 articles.
1. Monitoring Depth of Anesthesia Based on Hybrid Features and Recurrent Neural Network
2. Eye Blink Artifact Detection With Novel Optimized Multi-Dimensional Electroencephalogram Features
3. Adaptive drug interaction model to predict depth of anesthesia in the operating room
4. Refining Target-Controlled Infusion
5. Layer normalization;lei ba;arXiv 1607 06450,2016
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