Anesthesia depth prediction from drug infusion history using hybrid AI

Abstract Background Accurately predicting the depth of anesthesia is essential for ensuring patient safety and optimizing surgical outcomes. Traditional regression-based approaches often struggle to model the complex and dynamic nature of patient responses to anesthetic agents. Machine learning tech...

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Hlavní autoři:	Liang Wang, Yiqi Weng, Wenli Yu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	BMC 2025-04-01
Edice:	BMC Medical Informatics and Decision Making
Témata:	Depth of anesthesia Deep learning Drug infusion history LSTM Transformers Kolmogorov-Arnold Networks
On-line přístup:	https://doi.org/10.1186/s12911-025-02986-w
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