Machine learning based method for the evaluation of the Analgesia Nociception Index
A research was conducted on the analysis of the information provided by ANI as a valuable tool to replicate the actions of the anesthesiologist in remifentanil analgesia. The results of this research evidenced that including information about the minimum values of ANI together with the hemodynamic information outperformed the decisions made regarding only non-specific traditional signs such as heart rate and blood pressure. In addition, it was shown that including the ANI monitor in the decision-making process may anticipate a dose change to prevent hemodynamic events.
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