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A computationally efficient Hill curve adaptation strategy during continuous monitoring of dose-effect relation in anaesthesia

(2018) NONLINEAR DYNAMICS. 92(3). p.843-852
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Abstract
This paper discusses a possibility to simplify the number of parameters in the Hill curve by exploiting special mathematical functions. This simplification is relevant when adaptation is required for personalized model-based medicine during continuous monitoring of dose-response values. A mathematical framework of the involved physiology and modelling by means of distributed parameter progressions has been employed. Convergence to a unique dynamic response is achieved, allowing simplifying assumptions with guaranteed solution. Discussion on its use and comparison with other adaptation mechanism is provided.
Keywords
Hill curve, Continuous fraction expansion, Mathematical model, Nonlinear dynamics, Variability, Dose-effect relation, Patient specificity

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Please use this url to cite or link to this publication:

Chicago
Ionescu, Clara-Mihaela. 2018. “A Computationally Efficient Hill Curve Adaptation Strategy During Continuous Monitoring of Dose-effect Relation in Anaesthesia.” Nonlinear Dynamics 92 (3): 843–852.
APA
Ionescu, C.-M. (2018). A computationally efficient Hill curve adaptation strategy during continuous monitoring of dose-effect relation in anaesthesia. NONLINEAR DYNAMICS, 92(3), 843–852.
Vancouver
1.
Ionescu C-M. A computationally efficient Hill curve adaptation strategy during continuous monitoring of dose-effect relation in anaesthesia. NONLINEAR DYNAMICS. 2018;92(3):843–52.
MLA
Ionescu, Clara-Mihaela. “A Computationally Efficient Hill Curve Adaptation Strategy During Continuous Monitoring of Dose-effect Relation in Anaesthesia.” NONLINEAR DYNAMICS 92.3 (2018): 843–852. Print.
@article{8563698,
  abstract     = {This paper discusses a possibility to simplify the number of parameters in the Hill curve by exploiting special mathematical functions. This simplification is relevant when adaptation is required for personalized model-based medicine during continuous monitoring of dose-response values. A mathematical framework of the involved physiology and modelling by means of distributed parameter progressions has been employed. Convergence to a unique dynamic response is achieved, allowing simplifying assumptions with guaranteed solution. Discussion on its use and comparison with other adaptation mechanism is provided.},
  author       = {Ionescu, Clara-Mihaela},
  issn         = {0924-090X},
  journal      = {NONLINEAR DYNAMICS},
  keyword      = {Hill curve,Continuous fraction expansion,Mathematical model,Nonlinear dynamics,Variability,Dose-effect relation,Patient specificity},
  language     = {eng},
  number       = {3},
  pages        = {843--852},
  title        = {A computationally efficient Hill curve adaptation strategy during continuous monitoring of dose-effect relation in anaesthesia},
  url          = {http://dx.doi.org/10.1007/s11071-018-4095-3},
  volume       = {92},
  year         = {2018},
}

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