Neural network modeling to predict the hypnotic effect of propofol bolus induction.

Chao-Shun Lin, Yu-Chuan Li, Martin S. Mok, Chi-Cheng Wu, Hung-Wen Chiu, Yu Hwa Lin

研究成果: 雜誌貢獻文章

9 引文 (Scopus)

摘要

Dose requirements of propofol to achieve loss of consciousness depend on the interindividual variability. Until now when propofol was administered by a single bolus, how to define the optimal individual dose and to assess its hypnotic effect have not been clearly studied. The goal of this study is to develop an artificial neural network model to predict the hypnotic effect of propofol on the basis of common clinical parameters. Ten parameters were chosen as the input factors based on the related literatures and clinical experiences. The bispectral index of EEG was used to record the consciousness level of patients and served as the output factor. The predictive results of neural net models were superior to that of clinician. This model could potentially help determine the optimal dose of propofol and thus reduce the anesthetic cost.
原文英語
頁(從 - 到)450-454
頁數5
期刊Proceedings / AMIA ... Annual Symposium. AMIA Symposium
出版狀態已發佈 - 2002

指紋

Propofol
Hypnotics and Sedatives
Neural Networks (Computer)
Unconsciousness
Consciousness
Anesthetics
Electroencephalography
Costs and Cost Analysis

引用此文

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abstract = "Dose requirements of propofol to achieve loss of consciousness depend on the interindividual variability. Until now when propofol was administered by a single bolus, how to define the optimal individual dose and to assess its hypnotic effect have not been clearly studied. The goal of this study is to develop an artificial neural network model to predict the hypnotic effect of propofol on the basis of common clinical parameters. Ten parameters were chosen as the input factors based on the related literatures and clinical experiences. The bispectral index of EEG was used to record the consciousness level of patients and served as the output factor. The predictive results of neural net models were superior to that of clinician. This model could potentially help determine the optimal dose of propofol and thus reduce the anesthetic cost.",
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AU - Lin, Chao-Shun

AU - Li, Yu-Chuan

AU - Mok, Martin S.

AU - Wu, Chi-Cheng

AU - Chiu, Hung-Wen

AU - Lin, Yu Hwa

PY - 2002

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