An In-Depth Study of Personalized Anesthesia Management Models in Gastrointestinal Endoscopy Based on Multimodal Deep Learning

An In-Depth Study of Personalized Anesthesia Management Models in Gastrointestinal Endoscopy Based on Multimodal Deep Learning

In response to the annual occurrence of over 10 million gastrointestinal endoscopic examinations in China, this study proposes a personalized anesthesia management model based on multimodal deep learning. This model was designed to enhance anesthesia management efficiency and disease detection rates...

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Bibliographic Details
Main Authors: Hanqi Shi, Hongyu Wang, Xibing Ding, Zheng Dang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Gastrointestinal endoscopy
LSTM networks
hyperparameter optimization
sparse matrix classifier
real-time prediction
Online Access:https://ieeexplore.ieee.org/document/10829596/
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https://ieeexplore.ieee.org/document/10829596/

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