Modeling and Simulation in Medicine

Garant předmětu:

Raquel Cruz Conceicao

Přednášející:

Raquel Cruz Conceicao

Cvičící:

Raquel Cruz Conceicao, David Vrba, Jan Vrba

Předmět zajišťuje:

katedra biomedicínské techniky

Anotace:

This Course Unit aims to give students an introductory level knowledge of the methodologies available to model and simulate biological systems and their application in Medicine. At the end of this curricular unit, students should be able to: Identify the usefulness of modeling and simulation of physiological phenomena. Identify the main types of possible models, their advantages and limitations. Distinguish from the applicability of deterministic and stochastic models. Use simple methods to identify model parameters. Know the basic rules of operation and use of Monte Carlo simulation codes. Operate concepts in practical examples using MATLAB.

Požadavky:

In the case of foreign lecturers, there will be a weeklong block of intensive contact education for the number of students at least five. If the number of students is less than five, the course will be self-study with consultations using VoIP (e.g. Skype) and a contact 1-or 2-day seminar. The contact seminar will take place at the FBMI or at the home institution of a foreign lecturer. The subjects are concluded by an oral examination. The student must elaborate a paper on a given topic together with the exam in case of the controlled self-study.

Two laboratory exercises are required for admission to the exam (attested by a protocol signed by the student, the tutor and the supervisor of the course).

The protocols will be archived in the Department for Doctoral Studies.

Osnova přednášek:

Brief Syllabus of Lectures:

1.Physiological complexity and the need for models.

2.Models and the modeling process. What is a model? Why use models? How to model?

3.The process of data modeling. Formulation of models. Validation of modeling. Why and when to model the data.

4.The process of system modeling. (Static models. Linear models. Distributed models. Compartment models. Non-linear models. Time-varying models. Stochastic models.)

5.Model identification. Test signals. Errors. Estimation of parameters. Estimation of signals.

6.Parametric modeling: the identifiability problem and the estimation problem.

7.Validation of modeling methods.

8.Good practices and good modeling.

9.Monte Carlo simulation. (Random variables. Pseudorandom number generator. Inverse Transform method. Monte Carlo integration. Radiation transport: photoelectric effect, Rayleigh scattering).

10.Machine Learning Modeling.

Osnova cvičení:

Brief Syllabus of Exercises:

1.Good practices and good modeling - modeling of microwave coil.

2.Support Vector Machine for detection and classification of head stroke.

Cíle studia:

This Course Unit aims to give students an introductory level knowledge of the methodologies available to model and simulate biological systems and their application in Medicine. At the end of this curricular unit, students should be able to: Identify the usefulness of modeling and simulation of physiological phenomena. Identify the main types of possible models, their advantages and limitations. Distinguish from the applicability of deterministic and stochastic models. Use simple methods to identify model parameters. Know the basic rules of operation and use of Monte Carlo simulation codes. Operate concepts in practical examples using MATLAB.

Studijní materiály:

Required:

[1] Claudio Cobelli, Ewart Carson, „Introduction to Modeling in Physiology and Medicine“ - Academic Press Series in Biomedical Engineering, Elsevier, 2008, ISBN 978-0-12-160240-6

Recommended:

[1] M. Blomhoj, T.H. Kjeldsen, and J. Ottesen, "Compartment models”, 2005

[2] Luís Peralta, "Introdução aos métodos de simulação Monte Carlo no transporte da radiação”, Faculdade de Ciências, Universidade de Lisboa, 2010

Poznámka:

Modul E

Rozvrh na zimní semestr 2023/2024:

Rozvrh není připraven

Rozvrh na letní semestr 2023/2024:

Rozvrh není připraven

Předmět je součástí následujících studijních plánů: