MED M270D
Optimal Parameter Estimation and Experiment Design for Biomedical Systems
Medicine · 4 units · Graduate courses (200-299)
(Same as Bioengineering M296B, Biomathematics M270, and Computer Science M296B.) Estimation methodology and model parameter estimation algorithms for fitting dynamic system models to biomedical data. Model discrimination methods. Theory and algorithms for designing optimal experiments for developing and quantifying models, with special focus on optimal sampling schedule design for kinetic models. Exploration of PC software for model building and optimal experiment design via applications in physiology and pharmacology.
Letter grading.
Requisites
Official UCLA wording
Requisite: course M270C or Bioengineering CM286 or Biomathematics 220.
BruinTree reads · Prerequisite
needs reviewconfidence 0.90 · from text- · "BIOMATH 220" is not in this catalog version
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
MED M270D
- MED M270CAdvanced Modeling Methodology for Dynamic Biomedical Systems
- EC ENGR 141Principles of Feedback Control
- EC ENGR 102Systems and Signals
- MATH 115ALinear Algebra
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
MED M270D
- MED M270EAdvanced Topics and Research in Biomedical Systems Modeling and Computing
1 course lists this as a requisite. The whole downstream is here — 1 course over 1 level. Every course here opens its own tree.