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

Research output: Contribution to journalArticle

10 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)450-454
Number of pages5
JournalProceedings / AMIA ... Annual Symposium. AMIA Symposium
Publication statusPublished - 2002

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

Cite this

Neural network modeling to predict the hypnotic effect of propofol bolus induction. / Lin, Chao-Shun; Li, Yu-Chuan; Mok, Martin S.; Wu, Chi-Cheng; Chiu, Hung-Wen; Lin, Yu Hwa.

In: Proceedings / AMIA ... Annual Symposium. AMIA Symposium, 2002, p. 450-454.

Research output: Contribution to journalArticle

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