title: Adaptive fuzzy modeling of the hypnotic process in anesthesia.
abstract: This paper addresses the problem of patient model synthesis in anesthesia. Recent advanced drug infusion mechanisms use a patient model to establish the proper drug dose. However, due to the inherent complexity and variability of the patient dynamics, difficulty obtaining a good model is high. In this paper, a method based on fuzzy logic and genetic algorithms is proposed as an alternative to standard compartmental models. The model uses a Mamdani type fuzzy inference system developed in a two-step procedure. First, an offline model is obtained using information from real patients. Then, an adaptive strategy that uses genetic algorithms is implemented. The validation of the modeling technique was done using real data obtained from real patients in the operating room. Results show that the proposed method based on artificial intelligence appears to be an improved alternative to existing compartmental methodologies.
authors.affiliation: Department of Computer Science and System Engineering, Universidad de La Laguna, San Cristóbal de La Laguna, Tenerife, Spain.
authors.forename: A
authors.initials: A
authors.lastname: Marrero
authors.affiliation: Department of Computer Science and System Engineering, Universidad de La Laguna, San Cristóbal de La Laguna, Tenerife, Spain. jamendez@ull.edu.es.
authors.forename: J A
authors.initials: JA
authors.lastname: Méndez
authors.affiliation: Hospital Universitario de Canarias, San Cristóbal de La Laguna, Tenerife, Spain.
authors.forename: J A
authors.initials: JA
authors.lastname: Reboso
authors.affiliation: Department of Industrial Engineering, Universidad de La Laguna, San Cristóbal de La Laguna, Tenerife, Spain.
authors.forename: I
authors.initials: I
authors.lastname: Martín
authors.affiliation: Department of Industrial Engineering, Universidad de La Coruña, La Coruña, Spain.
authors.forename: J L
authors.initials: JL
authors.lastname: Calvo
mesh_terms: D000465:Algorithms; D000758:Anesthesia / Q000379:methods*; D000776:Anesthesiology; D000777:Anesthetics / Q000008:administration & dosage*; D001185:Artificial Intelligence; D003198:Computer Simulation; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D006991:Hypnosis, Anesthetic; D006993:Hypnotics and Sedatives / Q000008:administration & dosage*; D008297:Male; D015233:Models, Statistical; D016571:Neural Networks, Computer; D009873:Operating Rooms; D015742:Propofol / Q000008:administration & dosage; D012984:Software; D013997:Time Factors
chemical_list: D000777:Anesthetics; D006993:Hypnotics and Sedatives; D015742:Propofol
keywords: Anesthesia; Bispectral index; Fuzzy modeling; Genetic algorithms