[1] Nakayama M, Ichinose H, Yamamoto S, et al. The effect of fentanyl on hemodynamic and bispectral index changes during anesthesia induction with propofol[J]. J Clin Anesth, 2002, 14(2): 146–149.
[2] Tan ZB, Kaddoum R, Wang LY, et al. Decision-oriented multi-outcome modeling for anesthesia patients[J]. Open Biomed Eng J, 2010, 4: 113–122.
[3] Wang LY, Yin GG, Wang H. Identification of wiener models with anesthesia applications[J]. Int J Pure Appl Math Sci, 2004, 3: 35–61.
[4] Cihoric M, Tengberg LT, Bay-Nielsen M, et al. Prediction of outcome after emergency high-risk intra-abdominal surgery using the surgical Apgar score[J]. Anesth Analg, 2016, 123(6): 1516–1521.
[5] Moonesinghe SR, Mythen MG, Das P, et al. Risk stratification tools for predicting morbidity and mortality in adult patients undergoing major surgery: qualitative systematic review[J]. Anesthesiology, 2013, 119(4): 959–981.
[6] Le Manach Y, Collins G, Rodseth R, et al. Preoperative score to predict postoperative mortality (POSPOM): derivation and validation[J]. Anesthesiology, 2016, 124(3): 570–579.
[7] Fitzgerald M, Cameron P, Mackenzie C, et al. Trauma resuscitation errors and computer-assisted decision support[J]. Arch Surg, 2011, 146(2): 218–225.
[8] Grassi FR, Rapone B, Catanzaro FS, et al. Effectiveness of computer-assisted anesthetic delivery system (STATM) in dental implant surgery: a prospective study[J]. ORAL Implantol, 2017, 10(4): 381–389.
[9] Wang LY, Wang H, Yin GG. System for identifying patient response to anesthesia infusion: US, 8998808[P]. 2015-04-01.
[10] Wang LY, Wang H, Yin GG. Anesthesia infusion models: knowledge-based real-time identification via stochastic approximation[C]//Proceedings of the 41st IEEE Conference on Decision and Control. Las Vegas: IEEE, 2002.
[11] Gentilini A, Rossoni-Gerosa M, Frei CW, et al. Modeling and closed-loop control of hypnosis by means of bispectral index (BIS) with isoflurane[J]. IEEE Trans Biomed Eng, 2001, 48(8): 874–889.
[12] Furutani E, Sawaguchi Y, Shirakami G, et al. A hypnosis control system using a model predictive controller with online identification of individual parameters[C]//Proceedings of 2005 IEEE Conference on Control Applications. Toronto, Canada: IEEE, 2005.
[13] Dong C, Kehoe J, Henry J, et al. Closed-loop computer controlled sedation with propofol[C]//Proceedings of 1999 Anaesthetic Research Society. Edinburg, 1999: 631.
[14] Glen JB, Schwilden H, Stanski DR. Workshop on safe feedback control of anesthetic drug delivery. Schloss Reinhartshausen, Germany. June 29, 1998[J]. Anesthesiology, 1999, 91(2): 600–601.
[15] Nunes CS, Mahfouf M, Linkens DA, et al. Modelling and multivariable control in anaesthesia using neural-fuzzy paradigms: Part I. Classification of depth of anaesthesia and development of a patient model[J]. Artif Intell Med, 2005, 35(3): 195–206.
[16] Lin HH, Beck CL, Bloom MJ. On the use of multivariable piecewise-linear models for predicting human response to anesthesia[J]. IEEE Trans Biomed Eng, 2004, 51(11): 1876–1887.
[17] Shieh JS, Abbod MF, Hsu CY, et al. Monitoring and control of anesthesia using multivariable self-organizing fuzzy logic structure[M]//Jin YC, Wang LP. Fuzzy Systems in Bioinformatics and Computational Biology. Berlin, Heidelberg: Springer, 2009: 273-295.
[18] Sreenivas Y, Lakshminarayanan S, Rangaiah GP. Automatic regulation of anesthesia by simultaneous administration of two anesthetic drugs using model predictive control[M]//Magjarevic R, Nagel JH. World Congress on Medical Physics and Biomedical Engineering 2006. Berlin, Heidelberg: Springer, 2007: 82-86.
[19] Magjarevic R, Nagel JH. World congress on medical physics and biomedical engineering 2006[M]. Berlin, Heidelberg: Springer, 2006, doi: 10.1007/978-3-540-36841-0_28.