Module Number

MEDZ-4523
Module Title

Machine Learning to Fight Infections
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 Irregular
Language of instruction English
Type of Exam

Oral presentation and written report

Content

Machine learning is used in many areas of medicine to automate certain processes, find intelligent representations of complex data, and make predictions about phenotypes of interest or other labels. Machine learning techniques have also been applied and developed in infection research for quite some time. In this seminar, we will cover several areas ranging from Machine Learning assisted Computational Epidemiology, to Resistance Prediction of Infectious Agents, to Predicting Viral Evolution.

Objectives

The students know and can critically reflect the most important concepts, theories and methods in how to control infections with machine learning metho

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

-

Last offered unknown
Planned for Sommersemester 2024
Assigned Study Areas BIO-BIO, BIO-SEM, INFO-INFO, MEDI-APPL, MEDI-INFO, MEDZ-SEM, ML-CS