Module Number

ML-4506 		Module Title

Machine Learning for Medical Image Analysis 		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 graded participation in paper discussion
Content

The seminar starts with an introductory lecture to provide a compact overview of the research field (machine learning for medical image analysis), as well as a tutorial on critical analysis and presentation of research papers.
Throughout the remainder of the course, each student presents a paper from a collection of seminal work in the field. To foster engaging scientific exchange, each presented paper will have designated critics who are also tasked with studying the paper and preparing questions for its discussion.
Objectives

The learning objectives of this seminar consist of three parts: (1) the students will gain a solid understanding of key contributions to the field of machine learning for medical image analysis, (2) the students learn to critically read and analyse original research papers and judge their impact, and (3) the students will improve their scientific communication skills with an oral presentation and participation in discussions sessions.
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 Baumgartner, Koch
Literature

Will be provided in the course
Last offered Wintersemester 2022
Planned for Wintersemester 2023
Assigned Study Areas INFO-INFO, MEDI-APPL, MEDI-INFO, MEDZ-SEM, ML-CS, ML-DIV