Overview
About This Course
CACoM (Clinical Applications of Computational Medicine) is a project-based course at the Technical University of Munich, where students work in small teams to design, execute, and present data-driven research projects at the intersection of computation and clinical medicine.
:::danger CACoM's Guiding Idea At its core, CACoM is guided by a simple but powerful idea:
Improving human health.
If your project contributes to that goal — even in a small, indirect, or exploratory way — you are very likely moving in the right direction. :::
In addition to the project work, the course includes lectures by internal instructors and guest talks from clinicians, researchers, and industry partners. These sessions introduce students to diverse real-world applications of computational medicine and illustrate how data science, statistics, and engineering are transforming modern healthcare.
By the end of the course, you will have learned to formulate a research question, identify and analyze relevant data, apply appropriate computational methods, and communicate findings effectively to both technical and medical audiences.
:::info A(n) (Im)Modest Expectation
By the end of the semester, we hold an immodest expectation — that many of you will look back and consider CACoM the best course you’ve taken at TUM.
(That's not just wishful thinking — it's based on feedback from previous cohorts in our course evaluations. Just see here and here)
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:::tip Start Here If you're new, begin with the Schedule and then check the Project Proposal Guide. :::
Course Format
- Lectures — covering clinical and computational foundations.
- Student projects — 1–7 students per team, mentored by staff.
- Guest talks — from clinicians, researchers, and industry experts.
- Final presentations — 1-minute video + poster session.
Learning Outcomes
By completing CACoM, you will:
- Understand how computational methods are applied in modern medicine.
- Gain experience managing small, interdisciplinary research projects.
- Develop presentation and scientific communication skills.
- Appreciate how computation can meaningfully contribute to improving human health.