Module Number

MEDZ-4522 		Module Title

Machine Learning for Health 		Lecture Type(s)

Seminar
ECTS 3
Work load
- Contact time
- Self study
Workload:
90 h
Class time:
30 h / 2 SWS
Self study:
60 h
Duration 1 Semester
Frequency In the winter semester
Language of instruction English
Type of Exam

Oral presentation and written report
Content

This seminar covers different state-of-the-art machine learning methods on biomedical
data to answer medical questions of interest. This can include:
• Graphical model structure learning and causality in medicine
• Deep learning approaches in medicine
• Machine learning methods for small sample sizes
Objectives

Machine Learning for Health: Successful students know the most important terms, theories and methods in
the field of fighting infections with computer science methods and know how
to critically reflect on them.
Allocation of credits / grading
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Prerequisite for participation There are no specific prerequisites.
Lecturer / Other Pfeifer
Literature

The papers will be announced at the first meeting. / recommended: Machine learning: theory and algorithms or Introduction to Statistical
Machine Learning for Bioinfos and Medicine Infos
Last offered Wintersemester 2022
Planned for Wintersemester 2023
Assigned Study Areas INFO-INFO, MEDI-APPL, MEDI-INFO, MEDZ-SEM, ML-CS, ML-DIV