Modelação e Simulação em Medicina (Fcul)

Objectives

This Curricular Unit aims to: A - Give students an introductory level knowledge of the methodologies available to model and simulate biological systems and their application in Medicine. B - Identify the usefulness of modeling and simulating physiological phenomena. Identify the main types of possible models, their advantages and limitations. C - Distinguish from the applicability of deterministic and stochastic models. D - Use simple methods to identify model parameters. E – Application of machine learning models. F - Know the basic rules of operation and use of Monte Carlo simulation codes and operationalize the concepts in practical examples using MATLAB.

Syllabus

1 - Physiological complexity and the need to use models. Models and the modeling process. What is a model? Why use templates? How to model? The process of creating models. Model formulation. Modeling validation. 2 - The bases of modeling and data. Why and when to model the data. Alternatives to data modeling. Modeling a single variable that occurs spontaneously. Modeling a single variable subject to perturbations. Modeling of two correlated variables. Modeling of control signals. 3 - Impulse response and deconvolution. Static models. Linear models. Distributed models. Nonlinear models. Models for time-varying processes. Stochastic models. Model identification. Parameter estimation. Model identifiability. 4 - Errors. The direct problem. Validation of modeling methods. Good practices and good modeling. Examples. 5 – Modeling physiological models with machine learning algorithms