MS1SOM - Decision Making Systems in Medicine

Course specification
Course title Decision Making Systems in Medicine
Acronym MS1SOM
Study programme Electrical Engineering and Computing
Module Signals and Systems
Type of study master academic studies
Lecturer (for classes)
    Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition none
    The goal Objective of the course is for the students to be informed about the statistical methods for pattern recognition in terms of medicine: hypothesis testing, parametric and nonparametric classification, clustering.
    The outcome Learning outcomes of the course are following: students´ ability to generate or to collect high quality and informative training sets of data, to apply appropriate statistical pattern recognition technique (hypothesis testing, parametric or nonparametric classifier), to design system for data clustering.
    Contents of lectures Probability decision-making methods. Evaluation of competing hypotheses Bayesian analysis. Inductive methods based on the minimization of risk. Decision-making methods based on explicit knowledge. Evaluation decision system.
    Contents of exercises Mastering software support for empirical inductive decisions, selecting the most informative attributes in the decision-making process, and evaluating the effectiveness of synthesized systems.
    1. R.O.Duda, P.E.Hart, "Pattern Classification", Second Edition, John Waley & Sons, 2001. (Original title)
    2. T.Hastie, R. Tibshirani, J. Friedman, "The Elements of Statistical Learning, Data Mining, Inference, and Prediction", Springer, 2001. (Original title)
    3. C.M.Bishop, "Pattern Recognition and Machine Learning", Springer, 2006. (Original title)
    4. R.P.W. Duin, P. Juszczak, P. Paclik, E. Pekalska, D. de Ridder, D.M.J. Tax, PRTools4, A Matlab Toolbox for Pattern Recognition, Delft University of Technology, 2004. (Original title)
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 1 1
    Methods of teaching Lectures and auditory exercises.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 10 Test paper 30
    Practical lessons 30 Oral examination 0
    Projects 0
    Colloquia 30
    Seminars 0