Master Seminar: ML for Medical Data — SS 2025

Master Seminar: Machine Learning for Medical Data, Summer Semester 2025

Instructors: Prof. Dr. Paul Swoboda (responsible), Jan Benedikt Ruhland (lecturer)

Language: English

Credits: 5 CP

Workload: 60 hours total (30 hours contact time, 120 hours self-study)

Format: Seminar, 2 SWS

Enrollment: Limited to 24 participants

Frequency: Irregular

Duration: 1 Semester

Course Content

Discriminative and generative models, biomarker discovery, causality, LLMs and omics, industrial applications and other ML implementations in medical contexts.

Learning Outcomes

Students demonstrate comprehensive knowledge of contemporary and established advances in ML for medical applications. They develop the capability to independently assess scientific publications and deliver technical presentations.

Prerequisites

Background in machine learning is essential.

Participation Requirements

• Consistent in-person attendance
• Individual topic presentation
• Active discussion involvement
• Written report submission
• Mid-term progress presentation

Assessment

Evaluation combines presentation quality and written report submissions.

Target Program

M.Sc. Artificial Intelligence and Data Science (primary); accessible to other programs.