NDLI: Dynamic models with quantized output for modeling patient response to pharmacotherapy

Content Provider	IEEE Xplore Digital Library
Author	Bjork, M. Medvedev, A. Stoica, P.
Copyright Year	2010
Description	Author affiliation: Division of Systems and Control, Department of Information Technology Uppsala University, Sweden (Bjork, M.; Medvedev, A.; Stoica, P.)
Abstract	This article presents a way of modeling patient response to a pharmacotherapy by means of dynamic models with quantized output. The proposed modeling technique is exemplified by treatment of Parkinson's disease with Duodopa $^{®},$ where the drug is continuously administered via duodenal infusion. Titration of Duodopa $^{®}$ is currently performed manually by a nurse judging the patient's motor symptoms on a quantized scale and adjusting the drug flow provided by a portable computer-controlled infusion pump. The optimal drug flow value is subject to significant inter-individual variation and the titration process might take up to two weeks for some patients. In order to expedite the titration procedure via automation, as well as to find optimal dosing strategies, a mathematical model of this system is sought. The proposed model is of Wiener type with a linear dynamic block, cascaded with a static nonlinearity in the form of a non-uniform quantizer where the quantizer levels are to be identified. An identification procedure based on the prediction error method and the Gauss-Newton algorithm is suggested. The datasets available from titration sessions are scarce so that finding a parsimonious model is essential. A few different model parameterizations and identification algorithms were initially evaluated. The results showed that models with four parameters giving accurate predictions can be identified for some of the available datasets.
Starting Page	1029
Ending Page	1034
File Size	411639
Page Count	6
File Format	PDF
ISBN	9781424453627
ISSN	10851992
DOI	10.1109/CCA.2010.5611215
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-08
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models Mathematical model Drugs Approximation methods Quantization Predictive models Accuracy
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

On sampled-data models for model predictive control

Model predictive control with integrated experiment design for output error systems

Approximate state estimation for linear systems with quantized data

Applying an Instance-Specific Model to Longitudinal Clinical Data for Prediction

A Direct Dynamic Dose-Response Model of Propofol for Individualized Anesthesia Care

Bayesian dynamic linear model-based modeling method for an aniline stripping column

Application and Construction of General Prediction Model for Drugs Marketing System

Analytical accuracy evaluation of fixed-point systems

Modeling cervix cancer growth and response to radiation therapy: A validation study using patient volumetric tumor data

Dynamic models with quantized output for modeling patient response to pharmacotherapy

Similar Documents

On sampled-data models for model predictive control

Model predictive control with integrated experiment design for output error systems

Approximate state estimation for linear systems with quantized data

Applying an Instance-Specific Model to Longitudinal Clinical Data for Prediction

A Direct Dynamic Dose-Response Model of Propofol for Individualized Anesthesia Care

Bayesian dynamic linear model-based modeling method for an aniline stripping column

Application and Construction of General Prediction Model for Drugs Marketing System

Analytical accuracy evaluation of fixed-point systems

Modeling cervix cancer growth and response to radiation therapy: A validation study using patient volumetric tumor data

Dynamic models with quantized output for modeling patient response to pharmacotherapy