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.
CITATION STYLE
Jove, E., Gonzalez-Cava, J. M., Casteleiro-Roca, J. L., Quintián, H., Méndez-Pérez, J. A., Calvo-Rolle, J. L., … Reboso, J. (2018). Remifentanil dose prediction for patients during general anesthesia. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10870 LNAI, pp. 537–546). Springer Verlag. https://doi.org/10.1007/978-3-319-92639-1_45
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