Najmeh Jamali - Department of Industrial Engineering, University of Torbat HeydariehTorbat Heydarieh, Iran
Hamideh Razavi - Department of Industrial Engineering, Faculty of Engineering Ferdowsi University of Mashhad, Iran

An adaptive neuro-fuzzy inference system is applied to assign the optimal anesthesia drug dose based on the type and time of the surgery according to the patients' needs. In this paper, the drug dose is estimated and optimized by applying the administration of anesthesia drug dosage without the Bispectral index (BIS). This paper introduces an intelligence auto-estimator to optimize the total amount of drug dose during general anesthesia. The optimized auto- estimator provides significant superiority for the patient in reducing the risk for under and over dosing during general anesthesia. A real case study of Mashhad hospital, Iran is provided. These patients' data representative of populations is used to validate the estimator by sensitivity analysis techniques. The results represent a suitable dose with a significant reduction is obtained. In conclusion, an optimal dosage estimator provides a fast induction time with an acceptable overshoot, decreases the total dosage induced, and also a satisfactory disturbance injection performance during anesthesia.

Anesthesia drug dose, Adaptive neuro-fuzzy inference system, Optimization, BIS.