Remifentanil Dose Prediction for Patients During General Anesthesia View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-06-08

AUTHORS

Esteban Jove , Jose M. Gonzalez-Cava , José-Luis Casteleiro-Roca , Héctor Quintián , Juan Albino Méndez-Pérez , José Luis Calvo-Rolle , Francisco Javier de Cos Juez , Ana León , María Martín , José Reboso

ABSTRACT

In the anesthesia field there are some challenges, such as achieving new methods to control, and, of course, for reducing the pain suffered for the patients during surgeries. The first steps in this field were focused on obtaining representative measurements for pain measurement. Nowadays, one of the most promiser index is the ANI (Antinociception Index). This research works deals the model for the remifentanil dose prediction for patients undergoing general anesthesia. To do that, a hybrid model based on intelligent techniques is implemented. The model was trained using Support Vector Regression (SVR) and Artificial Neural Networks (ANN) algorithms. Results were validated with a real dataset of patients. It was possible to check the really successful model performance. More... »

PAGES

537-546

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-92639-1_45

DOI

http://dx.doi.org/10.1007/978-3-319-92639-1_45

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104468631


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