Methods in Medical Informatics

Teaching in Medical Informatics


Find below our courses and further information you will find useful during the program.

Introductory Slides (Medical Informatics Master's)

Link to slides

New students in the Medical Informatics Master's program: please see Prof. Pfeifer's  Welcome message and information slides.
 

Current Semester Courses

WINTER 2024/2025

Please check if your course takes place online or in presence, there might be changes during the semester.

  • Preparatory Course in Programming for Medical/Life Scientists
     
  • Lecture: Advanced Medical Informatics
    This lecture comprises different areas of Medical Informatics. The focus is on data integration, medical data privacy, artificial intelligence and data mining for health data, and treatment decision support systems.
     
  • Lecture: Medical Data Science
    This lecture comprises different areas of Medical Data Science. Data Science or statistical Machine Learning methods have the potential to transform personal health care over the coming years. Advances in the technologies have generated large biological data sets. To gain insights that can then be used to improve preventive care or treatment of patients, these big data have to be stored in a way that enables fast querying of relevant characteristics of the data and consequently building statistical models that represent the dependencies between variables. These models can then be utilized to derive new biomedical principals, provide evidence for or against certain hypotheses, and to assist medical professionals in their decision process. Specific topics are
    • Gaining new insights from medical data
    • Modeling uncertainty in medical data science models
    • Making medical findings available through interpretable decision support systems

      Method-wise, the lecture introduces methods for
    • GWAS analyses (e.g., LMMs),
    • sequence analysis (e.g., kernel methods),
    • small n problems (e.g., domain adaptation, transfer learning, and multitask learning),
    • data integration (advanced unsupervised learning methods),
    • learning probabilistic Machine Learning models (e.g., graphical models),
    • large data sets (e.g., deep learning models)
       
  • Seminar: Machine Learning for Health
    This seminar covers different machine learning methods on biomedical data to answer medical questions of interest.
     
  • Seminar: Privacy-preserving Methods in Biomedical Studies: Data Privacy
     
  • Practical course: Secure Processing of Medical Data: Privacy-Enhancing Technologies in Practice
     

SUMMER 2024

  • Lecture: Bioinformatics for Life Scientists
     
  • Lecture: Introduction to Statistical Machine Learning for Bioinformaticians and Medical Informaticians
    This lecture provides an introduction into statistical machine learning with a focus on practical application in (biomedical) data analysis. It comprises basic methods for supervised (classification, regression) and unsupervised learning. Topics include but are not limited to: Linear models for regression and classification, model selection & regularization, cross validation, bootstrap, decision trees, random forest, boosting, support vector machines, dimensionality reduction, clustering methods. Programming tasks require submission in R.
     
  • Lecture: Introduction to Cryptography
    Cryptography is today an essential part of the security of all modern communications, secure data storage, and confidential computing. This course will provide an introduction to all of the most fundamental principles, methods, and definitions in the field of cryptography, in addition to a review of some of the most important applications.
     
  • Seminar: Machine Learning to Fight Infections
    This seminar covers different machine learning methods on biomedical data to answer medical questions of interest.
     
  • Practical course: Machine Learning in Biomedicine
     

See also: IBMI Programming Helpdesk with focus on Java and Python.
 

Previous Teaching

WINTER 2023/2024

SUMMER 2023

WINTER 2022/2023

SUMMER 2022

WINTER 2021/2022

  • Lecture: Advanced Medical Informatics
  • Lecture: Medical Data Science
  • Seminar: Machine Learning for Health
  • Practical Course: Software Development with Scrum
     

SUMMER 2021

WINTER 2020/2021

SUMMER 2020

WINTER 2019/2020

  • Lecture: Advanced Medical Informatics
  • Practical Course: Machine Learning in Biomedicine
  • Seminar: Machine Learning for Health
  • Seminar: Biomedical Informatics Methods for Infection Research
     

SUMMER 2019

  • Lecture: Medical Data Science
  • Lecture: Bioinformatics for Life Scientists
  • Seminar: Computer Science Methods for Privacy Preservation and Personalized Medicine
  • Seminar: Probabilistic Graphical Models and Probabilistic Programming
  • Software Project in Medical Informatics
     

WINTER 2018/2019

  • Lecture: Advanced Medical Informatics
  • Practical course: Machine Learning in Biomedicine
  • Seminar: Machine Learning for Health
     

SUMMER 2018

  • Lecture: Medical Data Science
  • Lecture: Bioinformatics for Life Scientists
  • Seminar: Computer Science Methods for Privacy Preservation in Biomedical Studies
  • Software Project in Medical Informatics
     

WINTER 2017/2018

  • Lecture: Advanced Medical Informatics
  • Practical course: Machine Learning in Biomedicine
  • Seminar: Machine Learning for Health
     

SUMMER 2017

  • Lecture: Medical Data Science
  • Seminar: Biomedical Informatics Methods for Infection Research
  • Software Project in Medical Informatics
     

Thesis Topics

We are offering a range of topics for Master’s and Bachelor’s theses and research projects.

Feel free to check our group members’ research interests, and contact us to explore your area for supervision together.

You can download our Medical Informatics (or Bioinformatics) Master's Thesis Template here.

We are looking forward to discussing further details with you!
 

Semester Abroad

If you are interested in completing a semester of our degree program outside Germany, please find all details at Studying Abroad.