A solution to get the problem off, have you found it? Really? What kind of solution do you resolve the problem? From what sources? Well, there are so many questions that we utter every day. No matter how you will get the solution, it will mean better. You can take the reference from some books. And the compartmental models and their application is one book that we really recommend you to read, to get more solutions in solving this problem.

Compartmental models and their application

Type 1 diabetes mellitus is a disease affecting millions of people worldwide and causing the expenditure of millions of euros every year for health care. One of the most promising therapies derives from the use of an artificial pancreas, based on a control system able to maintain the normoglycaemia in the subject affected by diabetes. A dynamic simulation model of the glucose-insulin system can be useful in several circumstances for diabetes care, including testing of glucose sensors, insulin infusion algorithms, and decision support systems for diabetes. This paper considers the problem of the identification of single individual parameters in detailed dynamic models of glucose homeostasis. Optimal model-based design of experiment techniques are used to design a set of clinical tests that allow the model parameters to be estimated in a statistically sound way, while meeting constraints related to safety of the subject and ease of implementation. The model with the estimated set of parameters represents a specific subject and can thus be used for customized diabetes care solutions. Simulated results demonstrate how such an approach can improve the effectiveness of clinical tests and serve as a tool to devise safer and more efficient clinical protocols, thus providing a contribution to the development of an artificial pancreas.

Optimal Design of Clinical Tests for the Identification of Physiological Models of Type 1 Diabetes Mellitus

Optimal design of clinical tests for the identification of physiological models of type 1 diabetes mellitus in the presence of model uncertainty

A model-based experiment design techniques is used to design improved test protocols for the identification of the parameters of a detailed physiological models of diabetes specific to single subjects This paper considers the problem of parameter identification focusing on the impact of some decision variables such as sampling frequency and test duration on both the design effectiveness and the ability to meet safety critical constraints on the subject response The proposed methodology permits to establish the minimal experimental budget required to achieve a satisfactory parameter estimation from the planned test without upsetting the subject excessively

As a result of the severe practical and ethical con- straints imposed on medical measurements, the parameter estima- tion procedure designed for diagnosis and therapy is often a difficult problem. When blood sampling provides the data, the number of samples and the observation interval should be minimized. Design- ing an experiment for parameter estimation requires a step known as quantitative experiment design, usually preceded by a step called qualitative experiment design. The latter answers if a model is identifiable under particular experimental conditions. The former is suitable for the purpose of obtaining the maximum information from the data to be collected. An experiment design is based on the optimization of a suitable criterion formulated with respect to the analyzed variables of the experiment (input shape, sampling sched- ule). This paper considers sampling schedule design. New criteria for new optimal sampling schedules (OSS) have been formulated on the basis of sensitivity function. These are referred to as S-OSS and RS-OSS designs. The results of optimization for both criteria are compared with the result obtained with a reputable established D- optimal design based on the Fisher information matrix. By showing the results of S-OSS and RS-OSS design we can present the reliabil- ity and efficiency of the new criteria in comparison to D-OSS design. Illustrative examples are presented.

/pdf/a-new-oss-design-based-on-parameter-sensitivity-to-changes-1q9la5yh2z.pdf

A new OSS design based on parameter sensitivity to changes in measurements

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

D. Bochen

Author Tools

Chat about Author

Papers

A new OSS design based on parameter sensitivity to changes in measurements