Machine-learning Algorithm to Differentiate Intraoperative Ketamine Dosing Based on Electroencephalographic Density Spectrum Array Analysis

Abstract

Ketamine is widely used in the setting of multimodal general anesthesia, and the Electroencephalographic density spectral array (DSA) monitoring has been implemented in the practice of anesthesia. The purpose of this study is to investigate the dose-response EEG changes in patients during the perioperative period when ketamine is used. With the application of machine-learning algorithm, we aim to interpret the ketamine dosing precisely and accurately, based on the DSA obtained.

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